Error-rate assessment

Take all the input files, attach their unique_id, find the ones with replicates, then look at the median of 2*SD (~95% spread around measurement mean) for all measurements to decided on an approriate significance threshold

file_vector = str_remove(list.files(path = "Input", pattern="*.csv", recursive = T), ".csv")

error_set = lapply(paste0("Input/", list.files(path = "Input", pattern="*.csv", recursive = T)), read_csv, skip = 5, col_names = F, col_select = 1:2, show_col_types=F)

for(i in 1:length(error_set)){
  error_set[[i]][,3] = file_vector[i]
}

error_set = do.call("rbind", error_set)

colnames(error_set) = c("Genotype", "Phenotype", "unique_id")

error_rates = error_set[which(duplicated(error_set %>% 
  unite(unique_geno, c(1,3), sep = "_", remove = F) %>%
  pull(unique_geno))),] %>%
  group_by(Genotype) %>%
  summarise(pheno_mean = mean(Phenotype),
            pheno_sd = sd(Phenotype))

## % of SDs for measurements that are less than 1.5-fold threshold

sum(error_rates$pheno_sd*2 <= log10(1.5)) / length(error_rates$pheno_sd)
## [1] 0.5170068
median(error_rates$pheno_sd*2)
## [1] 0.1705538
summary(error_rates$pheno_sd*2)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## 0.00000 0.08511 0.17055 0.71405 0.74638 3.73452
error_rates %>%
  ggplot(aes(x = pheno_sd*2)) +
  geom_histogram(bins = 50) +
  geom_vline(xintercept = log10(1.5), lty = 2) +
  theme_classic() +
  theme(text = element_text(size=18), axis.text = element_text(size = 16, color = "black"),
        axis.title.y = element_blank(),
        axis.title.x = element_blank(),
        legend.position = "none")

## Fold-Change Data

Here we look at the fold-change data used in the input files. This allows us to see positive and negative functional effects across the landscapes.

fit_land = do.call("rbind", lapply(paste0("Output/", list.files(path = "Output", pattern="observed_values.csv", recursive = T)), read_csv, skip = 1, show_col_types=F, col_names = c("id", "effect", "muts", "junk1", "junk2", "enz")))

## Make fit_land have IDs by finding where muts are 0, i.e. start of new dataset, and multiplying
## Those values by the folder names to generate ID vector

fit_land_spots = c(which(fit_land$muts == 0), (dim(fit_land)[1] + 1)) # Add end of dataset
fit_land_counts = c()

for(i in 1:(length(fit_land_spots) - 1)) {
  
  if(i == 1) {
    fit_land_counts = c(fit_land_counts, fit_land_spots[i + 1] - 1)
  } else {
    fit_land_counts = c(fit_land_counts, fit_land_spots[i + 1] - fit_land_spots[i])
  }

}

## This assumes folders are read in the order that they are listed

fit_land_ids = rep(str_remove_all(list.files(path = "Output", pattern="observed_values.csv", recursive = T), "/observed_values.csv"), fit_land_counts)

fit_land$unique_id = fit_land_ids

fit_land = fit_land %>% filter(muts != 0)

The data shows the following distribution

c(sum(fit_land$effect < log10(1/1.5)), sum(fit_land$effect >= log10(1/1.5) & fit_land$effect <= log10(1.5)), sum(fit_land$effect > log10(1.5)))
## [1] 360 292 807

And these percentages

c(sum(fit_land$effect < log10(1/1.5)), sum(fit_land$effect >= log10(1/1.5) & fit_land$effect <= log10(1.5)), sum(fit_land$effect > log10(1.5))) / sum(c(sum(fit_land$effect < log10(1/1.5)), sum(fit_land$effect >= log10(1/1.5) & fit_land$effect <= log10(1.5)), sum(fit_land$effect > log10(1.5))))
## [1] 0.2467443 0.2001371 0.5531186

Histogram

fit_land_plot = fit_land %>%
  ggplot(aes(x = effect)) +
  geom_histogram(bins = 100, alpha = 0.8, color = "black", lwd = 0.1) +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(1/1.5), lty = 2, lwd = 0.2) +
  theme_classic() +
  labs(x = expression(italic("F")), 
       y = "Genotype Counts") +
  scale_y_continuous(breaks = c(0, 50, 100, 150, 200, 250)) +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"))

fit_land_plot

#ggsave("supp_fig_1.svg", plot = fit_land_plot, width = 180/2, height = 247/4, dpi = 300, units = "mm")

Ratio Data

First we import the ratio datasets, which contains ratio values between predicted function based on the additive model vs observed function. These ratio values serve as a general metric for “epistasis” as defined by the additive model.

all_ratios = lapply(paste0("Output/", list.files(path = "Output", pattern="ratio_export.csv", recursive = T)), read_csv, skip = 1, show_col_types=F, col_names = c("id", "effect", "muts", "cv", "colors"))

all_ratios_id = str_remove_all(list.files(path = "Output", pattern="ratio_export.csv", recursive = T), "/ratio_export.csv")

temp_col_length = length(all_ratios[[1]]) + 1

for(i in 1:length(all_ratios)) {
  all_ratios[[i]][, temp_col_length] = rep(all_ratios_id[i], dim(all_ratios[[i]])[1]) ## Add partial_id as a column to each ratio df in list
}

rm(temp_col_length)

## Make into a tibble
all_ratios = do.call("rbind", all_ratios)
colnames(all_ratios) = c("id", "effect", "muts", "cv", "colors", "partial_id")

Filtering ratio data to only include genotypes with 2+ mutations. Outputting length of vector.

all_ratios = all_ratios %>% filter(muts > 1)

length(all_ratios$effect) # examined muts
## [1] 1245

Number and % of synergystic genotypes (i.e. ratio > 1.5-fold)

sum(all_ratios$effect > 1.5) # synergystic
## [1] 502
paste0("Synergystic ", round(sum(all_ratios$effect > 1.5)/length(all_ratios$effect)*100,2), "%", collapse = "") # synergystic %
## [1] "Synergystic 40.32%"

Number and % of neutral genotypes (i.e. ratio > 1.5-fold)

sum(all_ratios$effect >= 1/1.5 & all_ratios$effect <= 1.5) # antagonistic
## [1] 379
paste0("Neutral ", round(sum(all_ratios$effect >= 1/1.5 & all_ratios$effect <= 1.5)/length(all_ratios$effect)*100, 2), "%", collapse = "") # antagonistic %
## [1] "Neutral 30.44%"

Number and % of antagonistic genotypes (i.e. ratio > 1.5-fold)

sum(all_ratios$effect < 1/1.5) # antagonistic
## [1] 364
paste0("Antagonistic ", round(sum(all_ratios$effect < 1/1.5)/length(all_ratios$effect)*100, 2), "%", collapse = "") # antagonistic %
## [1] "Antagonistic 29.24%"

Histogram

Shows distribution of positive and negative epistasis across the landscapes. The significance threshold is 1.5-fold

all_ratios_plot = all_ratios %>%
  ggplot(aes(x = log10(effect))) +
  geom_histogram(bins = 100, alpha = 0.8, color = "black", lwd = 0.1) +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(1/1.5), lty = 2, lwd = 0.2) +
  theme_classic() +
  scale_fill_manual(values = c("grey")) +
  labs(x = expression("Observed" *italic(" F")*" / Predicted"*italic(" F")), 
       y = "Genotype Counts") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")


all_ratios_plot

#ggsave("supp_fig_2.svg", plot = all_ratios_plot, width = 180/2, height = 247/4, dpi = 300, units = "mm")

Also the ratios table. Here we create bins from -Inf to log10(1/1.5), i.e. -0.176, then the neutral range between log10(1/1.5) to log10(1.5), i.e. 0.176, then the positive range from 0.176 to Inf.

all_ratios %>%
  mutate(sign = cut(log10(effect), breaks = c(-Inf, log10(1/1.5), log10(1.5), Inf))) %>%
  count(sign) %>%
  mutate(percent = round(n/sum(n) * 100, 2))
## # A tibble: 3 × 3
##   sign               n percent
##   <fct>          <int>   <dbl>
## 1 (-Inf,-0.176]    364    29.2
## 2 (-0.176,0.176]   379    30.4
## 3 (0.176, Inf]     502    40.3

We can do the same thing for individual orders: 2nd, 3rd, and 4th order

2nd order

## 2nd step only

all_ratios_2 = all_ratios %>% filter(muts == 2)

length(all_ratios_2$effect) # examined muts
## [1] 419
sum(all_ratios_2$effect > 1.5) # synergystic
## [1] 135
paste0("Synergystic ", round(sum(all_ratios_2$effect > 1.5)/length(all_ratios_2$effect)*100, 2), "%", collapse = "") # synergystic %
## [1] "Synergystic 32.22%"
sum(all_ratios_2$effect >= 1/1.5 & all_ratios_2$effect <= 1.5) # antagonistic
## [1] 160
paste0("Neutral ", round(sum(all_ratios_2$effect >= 1/1.5 & all_ratios_2$effect <= 1.5)/length(all_ratios_2$effect)*100, 2), "%", collapse = "") # antagonistic %
## [1] "Neutral 38.19%"
sum(all_ratios_2$effect < 1/1.5) # antagonistic
## [1] 124
paste0("Antagonistic ", round(sum(all_ratios_2$effect < 1/1.5)/length(all_ratios_2$effect)*100, 2), "%", collapse = "") # antagonistic %
## [1] "Antagonistic 29.59%"

3rd order

## 3rd step only

all_ratios_3 = all_ratios %>% filter(muts == 3)

length(all_ratios_3$effect) # examined muts
## [1] 438
sum(all_ratios_3$effect > 1.5) # synergystic
## [1] 160
paste0("Synergystic ", round(sum(all_ratios_3$effect > 1.5)/length(all_ratios_3$effect)*100, 2), "%", collapse = "") # synergystic %
## [1] "Synergystic 36.53%"
sum(all_ratios_3$effect >= 1/1.5 & all_ratios_3$effect <= 1.5) # antagonistic
## [1] 120
paste0("Neutral ", round(sum(all_ratios_3$effect >= 1/1.5 & all_ratios_3$effect <= 1.5)/length(all_ratios_3$effect)*100, 2), "%", collapse = "") # antagonistic %
## [1] "Neutral 27.4%"
sum(all_ratios_3$effect < 1/1.5) # antagonistic
## [1] 158
paste0("Antagonistic ", round(sum(all_ratios_3$effect < 1/1.5)/length(all_ratios_3$effect)*100, 2), "%", collapse = "") # antagonistic %
## [1] "Antagonistic 36.07%"

4th order

## 4th step only

all_ratios_4 = all_ratios %>% filter(muts == 4)

length(all_ratios_4$effect) # examined muts
## [1] 267
sum(all_ratios_4$effect > 1.5) # synergystic
## [1] 127
paste0("Synergystic ", round(sum(all_ratios_4$effect > 1.5)/length(all_ratios_4$effect)*100, 2), "%", collapse = "") # synergystic %
## [1] "Synergystic 47.57%"
sum(all_ratios_4$effect >= 1/1.5 & all_ratios_4$effect <= 1.5) # antagonistic
## [1] 72
paste0("Neutral ", round(sum(all_ratios_4$effect >= 1/1.5 & all_ratios_4$effect <= 1.5)/length(all_ratios_4$effect)*100, 2), "%", collapse = "") # antagonistic %
## [1] "Neutral 26.97%"
sum(all_ratios_4$effect < 1/1.5) # antagonistic
## [1] 68
paste0("Antagonistic ", round(sum(all_ratios_4$effect < 1/1.5)/length(all_ratios_4$effect)*100, 2), "%", collapse = "") # antagonistic %
## [1] "Antagonistic 25.47%"

Positional Functional Contribution Data

Here we import the functional contribution of single positions (not combinations), which resembles first order analysis across all datasets.

## Reads all csvs in collated folder and combines them

d = do.call("rbind", lapply(paste0("Output/", list.files(path = "Output", pattern="*2d_box.csv", recursive = T)), read_csv, show_col_types=F, col_names = c("positions", "identity", "mut", "effects", "enzyme", "type", "cond")))


d1 = d %>% filter_all(any_vars(!is.na(.))) # removes rows with all NA before making unique ID

d1 = d1 %>%
  unite("unique_id", c(positions, enzyme, type, cond), remove = F)

d1 = d1 %>%
  unite("partial_id", c(enzyme, type, cond), remove = F)

Histogram

Spread of functional contributions of the positions. This shows whether introducing a mutation in a given position impacts the function positively or negatively (or neutral) across all backgrounds

d1_plot = d1 %>%
  ggplot(aes(x = effects)) +
  geom_histogram(bins = 100, alpha = 0.8, color = "black", lwd = 0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(1/1.5), lty = 2, lwd = 0.2) +
  theme_classic() +
  labs(x = expression(Delta*italic("F")), 
       y = "Genotype Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")


d1_plot

#ggsave("fig_1A.svg", plot = d1_plot, width = 180/2, height = 247/4, dpi = 300, units = "mm")

Density plots for each trajectory by enzymes

d1_plot_enz = d1 %>%
  ggplot(aes(x = effects, fill = enzyme)) +
  geom_density(alpha = 0.8, color = "black", lwd = 0.1) +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(1/1.5), lty = 2, lwd = 0.2) +
  theme_classic() +
  labs(x = expression(Delta*italic("F")), 
       y = "Genotype Count") +
  #scale_y_continuous(breaks = c(0, 50, 100, 150, 200, 250)) +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"))


d1_plot_enz

### For WT-normalized data

Load the same kind of data as d1 except that has been normalized do the \(\Delta\)F in the WT background

wt_rel_df = do.call("rbind", lapply(paste0("Output/", list.files(path = "Output", pattern="*wt_rel.csv", recursive = T)), read_csv, show_col_types=F, col_names = c("positions", "identity", "mut", "effects", "enzyme", "type", "cond")))


wt_rel_df = wt_rel_df %>% filter_all(any_vars(!is.na(.))) # removes rows with all NA before making unique ID

wt_rel_df = wt_rel_df %>%
  unite("unique_id", c(positions, enzyme, type, cond), remove = F) %>%
  unite("partial_id", c(enzyme, type, cond), remove = F)

Then we plot it

wt_rel_plot = wt_rel_df %>%
  filter(mut > 1) %>% # filter out first mutations which are by definition 0 delta F
  ggplot(aes(x = effects)) +
  geom_histogram(bins = 100, alpha = 0.8, color = "black", lwd = 0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(1/1.5), lty = 2, lwd = 0.2) +
  theme_classic() +
  labs(x = expression(Delta*italic("F ")*"(Single Mutant Normalized)"), 
       y = "Genotype Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")


wt_rel_plot

#ggsave("fig_1A.svg", plot = d1_plot, width = 180/2, height = 247/4, dpi = 300, units = "mm")

And again for density plots for each enzyme

wt_rel_plot_enz = wt_rel_df %>%
  mutate(Enzyme = enzyme) %>%
  filter(mut > 1) %>%
  ggplot(aes(x = effects, fill = Enzyme)) +
  geom_density(alpha = 0.8, color = "black", lwd = 0.1) +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(1/1.5), lty = 2, lwd = 0.2) +
  theme_classic() +
  labs(x = expression(Delta*italic("F ")*"(Single Mutant Normalized)"), 
       y = "Density") +
  scale_x_continuous(limits = c(-2.5, 2.5)) + # Same data omitted for better resolution
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"))


wt_rel_plot_enz
## Warning: Removed 77 rows containing non-finite values (stat_density).

Given this spread which percentage is significantly (using log10 1.5-fold cutoff) negative, neutral, and positive in that order

wt_rel_df %>%
  filter(mut > 1) %>%
  mutate(sign = cut(effects, breaks = c(-Inf, log10(1/1.5), log10(1.5), Inf))) %>%
  count(sign) %>%
  mutate(percent = round(n/sum(n) * 100, 2))
## # A tibble: 3 × 3
##   sign               n percent
##   <fct>          <int>   <dbl>
## 1 (-Inf,-0.176]    942    24.5
## 2 (-0.176,0.176]  1438    37.4
## 3 (0.176, Inf]    1470    38.2

Heterogenity in Spread

Looks at 2*SD of each position/combination across all orders to determine functional heterogeneity.

This gives us a quick look at the general spread of heterogenity values and their mean.

idio_d = do.call("rbind", lapply(paste0("Output/", list.files(path = "Output", pattern="idio_df", recursive = T)), read_csv, show_col_types=F))

traj_col = sapply(str_split(list.files(path = "Output", pattern="idio_df", recursive = T), "/"),"[[",1)

traj_col_len = sapply(lapply(paste0("Output/", list.files(path = "Output", pattern="idio_df", recursive = T)), read_csv, show_col_types=F), dim)[1,]

traj_col_full = c()
for(i in 1:length(traj_col)) {
  traj_col_full = c(traj_col_full, rep(traj_col[i], traj_col_len[i]))
}

idio_d$traj = traj_col_full

Order 1

idio_d_order_1 = idio_d %>%
  filter(mutations == "Order 1") %>%
  ggplot(aes(x = idiosync)) +
  geom_histogram(binwidth = 0.08, color = "black", lwd = 0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  labs(x = expression("2"*sigma), 
       y = "Position Count") +
  theme_classic() +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")

idio_d_order_1

#ggsave("fig_1B.svg", idio_d_order_1, width = 180/2, height = 247/4, dpi = 300, units = "mm")

First order positions which have a heterogeneity index > log10 1.5-fold, 2-fold, 5-fold, and 10-fold for adaptive trajectories

idio_d %>%
  filter(mutations == "Order 1") %>%
  mutate(idiosync_1.5 = idiosync > log10(1.5),
         idiosync_2 = idiosync > log10(2),
         idiosync_5 = idiosync > log10(5),
         idiosync_10 = idiosync > log10(10)) %>%
  group_by(mutations) %>%
  summarise(idiosync_sig_1.5 = sum(idiosync_1.5),
            idiosync_sig_2 = sum(idiosync_2),
            idiosync_sig_5 = sum(idiosync_5),
            idiosync_sig_10 = sum(idiosync_10),
            idiosync_total = length(idiosync),
            idiosync_1.5 = sum(idiosync_1.5)/length(idiosync_1.5) * 100,
            idiosync_2 = sum(idiosync_2)/length(idiosync_2) * 100,
            idiosync_5 = sum(idiosync_5)/length(idiosync_5) * 100,
            idiosync_10 = sum(idiosync_10)/length(idiosync_10) * 100
            ) %>%
  knitr::kable()
mutations idiosync_sig_1.5 idiosync_sig_2 idiosync_sig_5 idiosync_sig_10 idiosync_total idiosync_1.5 idiosync_2 idiosync_5 idiosync_10
Order 1 211 205 150 114 214 98.59813 95.79439 70.09346 53.27103

Order 2-4

Histogram to show heterogenity at Orders 2, 3, and 4 with the log10 1.5-fold significance threshold

Order 2

idio_d %>%
  filter(mutations == "Order 2") %>%
  ggplot(aes(x = idiosync)) +
  geom_histogram(binwidth = 0.08, fill = "#edae49", color = "black", lwd = 0.1) +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  labs(x = expression("2"*sigma), 
       y = "Genotype Count") +
  scale_x_continuous(limits = c(0,5)) + #Scale that will be applied for all orders later
  theme_classic() +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")
## Warning: Removed 2 rows containing non-finite values (stat_bin).
## Warning: Removed 1 rows containing missing values (geom_bar).

## Order 3

idio_d %>%
  filter(mutations == "Order 3") %>%
  ggplot(aes(x = idiosync)) +
  geom_histogram(binwidth = 0.08, fill = "#edae49", color = "black", lwd = 0.1) +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  labs(x = expression("2"*sigma), 
       y = "Genotype Count") +
  #scale_x_continuous(limits = c(0,5)) + #Scale that will be applied for all orders later
  theme_classic() +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")

Order 4

idio_d %>%
  filter(mutations == "Order 4") %>%
  ggplot(aes(x = idiosync)) +
  geom_histogram(binwidth = 0.08, fill = "#edae49", color = "black", lwd = 0.1) +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  labs(x = expression("2"*sigma), 
       y = "Genotype Count") +
  scale_x_continuous(limits = c(0,5)) + #Scale that will be applied for all orders later
  theme_classic() +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")
## Warning: Removed 14 rows containing non-finite values (stat_bin).
## Warning: Removed 1 rows containing missing values (geom_bar).

Order 2-4 in Facet Grid

idio_d_multi_plot = idio_d %>%
  filter(mutations != "Order 1" & mutations != "Order 5" & mutations != "Order 6") %>%
  ggplot(aes(x = idiosync)) +
  geom_histogram(binwidth = 0.2, color = "black", lwd = 0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  labs(x = expression("2"*sigma), 
       y = "Combination Count") +
  facet_grid(~ mutations) +
  scale_x_continuous(limits = c(0,5)) +
  theme_classic() +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")

idio_d_multi_plot # Data removed
## Warning: Removed 51 rows containing non-finite values (stat_bin).
## Warning: Removed 6 rows containing missing values (geom_bar).

#ggsave("fig_2A.svg", idio_d_multi_plot, width = 180, height = 247/4, dpi = 300, units = "mm")

What percentage of positions remain significantly heterogeneous (1.5-fold) at these orders?

idio_d %>%
  filter(mutations == "Order 2" | mutations == "Order 3" | mutations == "Order 4") %>%
  mutate(idiosync = idiosync > log10(1.5)) %>%
  group_by(mutations) %>%
  summarise(idiosync_sig = sum(idiosync),
            idiosync_total = length(idiosync),
            idiosync = sum(idiosync)/length(idiosync) * 100
            )
## # A tibble: 3 × 4
##   mutations idiosync_sig idiosync_total idiosync
##   <chr>            <int>          <int>    <dbl>
## 1 Order 2            413            419     98.6
## 2 Order 3            420            438     95.9
## 3 Order 4            240            245     98.0

What percentage of positions remain significantly heterogeneous (1.5-, 2-, 5-, and 10-fold) at all orders?

idio_d %>%
  filter(mutations == "Order 1" | mutations == "Order 2" | mutations == "Order 3" | mutations == "Order 4") %>%
  mutate(idiosync_1.5 = idiosync > log10(1.5),
         idiosync_2 = idiosync > log10(2),
         idiosync_5 = idiosync > log10(5),
         idiosync_10 = idiosync > log10(10)) %>%
  group_by(mutations) %>%
  summarise(idiosync_sig_1.5 = sum(idiosync_1.5),
            idiosync_sig_2 = sum(idiosync_2),
            idiosync_sig_5 = sum(idiosync_5),
            idiosync_sig_10 = sum(idiosync_10),
            idiosync_total = length(idiosync),
            idiosync_1.5 = sum(idiosync_1.5)/length(idiosync_1.5) * 100,
            idiosync_2 = sum(idiosync_2)/length(idiosync_2) * 100,
            idiosync_5 = sum(idiosync_5)/length(idiosync_5) * 100,
            idiosync_10 = sum(idiosync_10)/length(idiosync_10) * 100
            ) %>%
  knitr::kable()
mutations idiosync_sig_1.5 idiosync_sig_2 idiosync_sig_5 idiosync_sig_10 idiosync_total idiosync_1.5 idiosync_2 idiosync_5 idiosync_10
Order 1 211 205 150 114 214 98.59813 95.79439 70.09346 53.27103
Order 2 413 387 252 170 419 98.56802 92.36277 60.14320 40.57279
Order 3 420 374 199 130 438 95.89041 85.38813 45.43379 29.68037
Order 4 240 204 122 61 245 97.95918 83.26531 49.79592 24.89796

Heterogenity in Sign

Collects all \(\Delta\)Function data for all orders

higher_order_list = list.files(path = "Output", pattern="higher_box", recursive = T)

higher_df = data.frame()
for(higher_file in 1:length(higher_order_list)){
  Condition = str_split(str_split(higher_order_list[higher_file], "_")[[1]][3], "/")[[1]][1]
  Measurement = str_split(higher_order_list[higher_file], "_")[[1]][2]
  Enzyme = str_split(higher_order_list[higher_file], "_")[[1]][1]
  appending_file = read_csv(paste0("Output/", higher_order_list[higher_file]), show_col_types=F)
  appending_file$Condition = Condition
  appending_file$Measurement = Measurement
  appending_file$Enzyme = Enzyme
  higher_df = bind_rows(higher_df, appending_file)
}


higher_df = higher_df %>%
  unite("unique_id", c(pos, Condition, Measurement, Enzyme), remove = F) %>%
  unite("partial_id", c(Enzyme, Measurement, Condition), remove = F)

higher_all_sign_check = higher_df %>%
  filter(str_count(genotype, "x")/str_length(genotype) != 1) %>% # Remove interactions with no other backgrounds
  mutate(mutations = factor(paste("Order", mutations, sep = " "))) %>%
  group_by(unique_id, mutations) %>%
  summarise(min_effect = min(avg),
            max_effect = max(avg))

Assigning positive, neutral, negative, negative-neutral, positive-neutral, and negative-positive ‘types’ based on log10 1.5-fold threshold to every Order

threshold = 1.5

types = c()
for(each in 1:dim(higher_all_sign_check)[1]){
  if(higher_all_sign_check$min_effect[each] < log10(1/threshold)){
    # Negative branch
    if(higher_all_sign_check$max_effect[each] < log10(1/threshold)) {
      # Full negative
      types = c(types, "Negative")
    } else if(higher_all_sign_check$max_effect[each] <= log10(threshold)) {
      # Negative Neutral
      types = c(types, "Neutral Negative")
    } else {
      # Negative Positive
      types = c(types, "Positive Negative")
    }
  } else {
    # Neutral or Positive
    if(higher_all_sign_check$min_effect[each] > log10(threshold)) {
      # Full positive
      types = c(types, "Positive")
    } else if(higher_all_sign_check$max_effect[each] > log10(threshold)) {
      # Neutral Positive
      types = c(types, "Neutral Positive")
    } else {
      # Neutral
      types = c(types, "Neutral")
    }
  }
}

higher_all_sign_check$type = factor(types)

All outputs show position/combination numbers in each category, followed by the total sum of all probed positions/combinations at that order, and finally percentages of each category

Order 1

order_checker = higher_all_sign_check %>% 
  filter(mutations == "Order 1") %>%
  pull(type) 

order_checker_levels = c("Negative", "Neutral", "Positive", "Neutral Negative", "Neutral Positive", "Positive Negative")

summary(order_checker) 
##          Negative           Neutral  Neutral Negative  Neutral Positive 
##                 3                 2                16                35 
##          Positive Positive Negative 
##                21               137
sum(summary(order_checker)) 
## [1] 214
summary(order_checker) / length(order_checker) * 100
##          Negative           Neutral  Neutral Negative  Neutral Positive 
##         1.4018692         0.9345794         7.4766355        16.3551402 
##          Positive Positive Negative 
##         9.8130841        64.0186916
pie_df = tibble(names = factor(names(summary(order_checker)), levels = order_checker_levels), values = summary(order_checker))

pie_order_1 = ggplot(pie_df, aes(x="", y=values, fill=names))+ 
  geom_bar(width = 1, stat = "identity") +
  coord_polar("y") +
  theme_minimal() + 
  theme(axis.title.x = element_blank(), axis.title.y = element_blank(), panel.border = element_blank(), panel.grid=element_blank(), axis.ticks = element_blank(), plot.title=element_text(size=14, face="bold"))

pie_order_1

#ggsave("fig_1C.svg", pie_order_1, width = 180/2, height = 247/4, dpi = 300, units = "mm")

Order 2

order_checker = higher_all_sign_check %>% 
  filter(mutations == "Order 2") %>%
  pull(type) 

summary(order_checker) 
##          Negative           Neutral  Neutral Negative  Neutral Positive 
##                 5                 5                37                64 
##          Positive Positive Negative 
##                13               295
sum(summary(order_checker)) 
## [1] 419
summary(order_checker) / length(order_checker) * 100
##          Negative           Neutral  Neutral Negative  Neutral Positive 
##          1.193317          1.193317          8.830549         15.274463 
##          Positive Positive Negative 
##          3.102625         70.405728
pie_df = tibble(names = factor(names(summary(order_checker)), levels = order_checker_levels), values = summary(order_checker))

pie_order_2 = ggplot(pie_df, aes(x="", y=values, fill=names))+ 
  geom_bar(width = 1, stat = "identity") +
  coord_polar("y") +
  theme_minimal() + 
  theme(axis.title.x = element_blank(), axis.title.y = element_blank(), panel.border = element_blank(), panel.grid=element_blank(), axis.ticks = element_blank(), plot.title=element_text(size=14, face="bold"))

pie_order_2

#ggsave("fig_2B_1.svg", pie_order_2, width = 180/2, height = 247/4, dpi = 300, units = "mm")

Order 3

order_checker = higher_all_sign_check %>% 
  filter(mutations == "Order 3") %>%
  pull(type) 

summary(order_checker) 
##          Negative           Neutral  Neutral Negative  Neutral Positive 
##                16                10                64                59 
##          Positive Positive Negative 
##                52               237
sum(summary(order_checker)) 
## [1] 438
summary(order_checker) / length(order_checker) * 100
##          Negative           Neutral  Neutral Negative  Neutral Positive 
##          3.652968          2.283105         14.611872         13.470320 
##          Positive Positive Negative 
##         11.872146         54.109589
pie_df = tibble(names = factor(names(summary(order_checker)), levels = order_checker_levels), values = summary(order_checker))

pie_order_3 = ggplot(pie_df, aes(x="", y=values, fill=names))+ 
  geom_bar(width = 1, stat = "identity") +
  coord_polar("y") +
  theme_minimal() + 
  theme(axis.title.x = element_blank(), axis.title.y = element_blank(), panel.border = element_blank(), panel.grid=element_blank(), axis.ticks = element_blank(), plot.title=element_text(size=14, face="bold"))

pie_order_3

#ggsave("fig_2B_2.svg", pie_order_3, width = 180/2, height = 247/4, dpi = 300, units = "mm")

Order 4

order_checker = higher_all_sign_check %>% 
  filter(mutations == "Order 4") %>%
  pull(type) 

summary(order_checker) 
##          Negative           Neutral  Neutral Negative  Neutral Positive 
##                11                 5                50                42 
##          Positive Positive Negative 
##                10               127
sum(summary(order_checker)) 
## [1] 245
summary(order_checker) / length(order_checker) * 100
##          Negative           Neutral  Neutral Negative  Neutral Positive 
##          4.489796          2.040816         20.408163         17.142857 
##          Positive Positive Negative 
##          4.081633         51.836735
pie_df = tibble(names = factor(names(summary(order_checker)), levels = order_checker_levels), values = summary(order_checker))

pie_order_4 = ggplot(pie_df, aes(x="", y=values, fill=names))+ 
  geom_bar(width = 1, stat = "identity") +
  coord_polar("y") +
  theme_minimal() + 
  theme(axis.title.x = element_blank(), axis.title.y = element_blank(), panel.border = element_blank(), panel.grid=element_blank(), axis.ticks = element_blank(), plot.title=element_text(size=14, face="bold"))

pie_order_4

#ggsave("fig_2B_3.svg", pie_order_4, width = 180/2, height = 247/4, dpi = 300, units = "mm")

All Orders

Raw Values

higher_all_sign_check_table = higher_all_sign_check %>% 
  group_by(mutations) %>%
  count(type) %>%
  pivot_wider(names_from = type,
              values_from = n) %>%
  mutate(Total = sum(across("Negative":"Positive Negative"))) 

higher_all_sign_check_table %>% knitr::kable()
mutations Negative Neutral Neutral Negative Neutral Positive Positive Positive Negative Total
Order 1 3 2 16 35 21 137 214
Order 2 5 5 37 64 13 295 419
Order 3 16 10 64 59 52 237 438
Order 4 11 5 50 42 10 127 245
Order 5 5 4 12 18 6 39 84
Order 6 1 2 2 2 1 6 14

Percentages

higher_all_sign_check_table %>%
  mutate(Negative = Negative/Total*100,
         Neutral = Neutral/Total*100,
         `Neutral Negative` = `Neutral Negative`/Total*100,
         `Neutral Positive` = `Neutral Positive`/Total*100,
         Positive = Positive/Total*100,
         `Positive Negative` = `Positive Negative`/Total*100) %>%
  knitr::kable()
mutations Negative Neutral Neutral Negative Neutral Positive Positive Positive Negative Total
Order 1 1.401869 0.9345794 7.476636 16.35514 9.813084 64.01869 214
Order 2 1.193317 1.1933174 8.830549 15.27446 3.102625 70.40573 419
Order 3 3.652968 2.2831050 14.611872 13.47032 11.872146 54.10959 438
Order 4 4.489796 2.0408163 20.408163 17.14286 4.081633 51.83673 245
Order 5 5.952381 4.7619048 14.285714 21.42857 7.142857 46.42857 84
Order 6 7.142857 14.2857143 14.285714 14.28571 7.142857 42.85714 14

WT points to Mean Deviation

Purpose of this analysis was to determine the difference in \(\Delta\)Function between the WT-background contribution of a given position/combination and the mean contribution of a given position or combination

Histogram

The spread of all positional contribution vs mean differences for each Order (1-4)

higher_df_mean = higher_df %>%
  filter(mutations < 5) %>%
  filter(str_count(genotype, "x")/str_length(genotype) != 1) %>% # Remove interactions with no other backgrounds
  group_by(unique_id, partial_id) %>%
  summarise(avg = mean(avg))

devs = c()
sign_devs = c()
cur_mutations = c()
for(i in 1:dim(higher_df_mean)[1]) {
  curr_id = higher_df_mean$unique_id[i]
  devs = c(devs, abs( (higher_df %>% filter(!str_detect(genotype, "1")) %>% filter(unique_id == curr_id) %>% pull(avg)) - (higher_df_mean$avg[i]) ))
  cur_mutations = c(cur_mutations, (higher_df %>% filter(!str_detect(genotype, "1")) %>% filter(unique_id == curr_id) %>% pull(mutations)))
  sign_devs = c(sign_devs, ifelse( (((higher_df %>% filter(!str_detect(genotype, "1")) %>% filter(unique_id == curr_id) %>% pull(avg)) > log10(1.5) & (higher_df_mean$avg[i]) < log10(1/1.5)) | ((higher_df %>% filter(!str_detect(genotype, "1")) %>% filter(unique_id == curr_id) %>% pull(avg)) < log10(1/1.5) & (higher_df_mean$avg[i]) > log10(1.5))), T, F)) ## Check if WT is positive while average is negative or vice versa
}


devs_df_wt = data.frame(devs = devs, muts = cur_mutations, sign_devs = sign_devs)

## Add unique ID if the WT deviates from mean

devs_df_wt = devs_df_wt %>%
  mutate(unique_id = higher_df_mean$unique_id[row_number()]) %>%
  mutate(partial_id = higher_df_mean$partial_id[row_number()])

WT sign heterogenity for Order 1

How many WT points have sign deviation from the mean at the 1st order?

paste0(length(which(devs_df_wt %>% filter(muts == 1) %>% pull(sign_devs))), "/", length(devs_df_wt %>% filter(muts == 1) %>% pull(sign_devs)))
## [1] "7/214"
paste0(round(sum(devs_df_wt %>% filter(muts == 1) %>% pull(sign_devs)) / length(devs_df_wt %>% filter(muts == 1) %>% pull(sign_devs)) * 100, 2), "%")
## [1] "3.27%"

WT sign heterogenity for Order 2

How many WT points have sign deviation from the mean at the 2nd order?

paste0(length(which(devs_df_wt %>% filter(muts == 2) %>% pull(sign_devs))), "/", length(devs_df_wt %>% filter(muts == 2) %>% pull(sign_devs)))
## [1] "53/419"
paste0(round(sum(devs_df_wt %>% filter(muts == 2) %>% pull(sign_devs)) / length(devs_df_wt %>% filter(muts == 2) %>% pull(sign_devs)) * 100, 2), "%")
## [1] "12.65%"

WT sign heterogenity for Order 3

How many WT points have sign deviation from the mean at the 3rd order?

paste0(length(which(devs_df_wt %>% filter(muts == 3) %>% pull(sign_devs))), "/", length(devs_df_wt %>% filter(muts == 3) %>% pull(sign_devs)))
## [1] "34/438"
paste0(round(sum(devs_df_wt %>% filter(muts == 3) %>% pull(sign_devs)) / length(devs_df_wt %>% filter(muts == 3) %>% pull(sign_devs)) * 100, 2), "%")
## [1] "7.76%"

WT sign heterogenity for Order 4

How many WT points have sign deviation from the mean at the 4th order?

paste0(length(which(devs_df_wt %>% filter(muts == 4) %>% pull(sign_devs))), "/", length(devs_df_wt %>% filter(muts == 4) %>% pull(sign_devs)))
## [1] "12/245"
paste0(round(sum(devs_df_wt %>% filter(muts == 4) %>% pull(sign_devs)) / length(devs_df_wt %>% filter(muts == 4) %>% pull(sign_devs)) * 100, 2), "%")
## [1] "4.9%"

Next we move away from sign to normal distance heterogenity

WT heterogenity for Order 1

devs_df_wt_1_plot = devs_df_wt %>%
  filter(muts == 1) %>%
  ggplot(aes(x = devs)) +
  geom_histogram(binwidth=0.08, color = "black", lwd = 0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  labs(x = expression("Deviation from Positional Mean ("*Delta*italic("F")*")"),
       y = "Position Count") +
  theme_classic() +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")

devs_df_wt_1_plot

#ggsave("fig_1D.svg", devs_df_wt_1_plot, width = 180/2, height = 247/4, dpi = 300, units = "mm")

WT heterogenity for Order 2

devs_df_wt %>%
  filter(muts == 2) %>%
  ggplot(aes(x = devs)) +
  geom_histogram(binwidth=0.08, color = "black", lwd = 0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  theme_classic() +
  scale_x_continuous(limits = c(0, 3)) +
  labs(x = expression("Deviation from Combinatorial Mean ("*epsilon*")"),
       y = "Combination Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")
## Warning: Removed 1 rows containing non-finite values (stat_bin).
## Warning: Removed 1 rows containing missing values (geom_bar).

WT heterogenity for Order 3

devs_df_wt %>%
  filter(muts == 3) %>%
  ggplot(aes(x = devs)) +
  geom_histogram(binwidth=0.08, color = "black", lwd = 0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  scale_x_continuous(limits = c(0, 3)) +
  theme_classic() +
  labs(x = expression("Deviation from Combinatorial Mean ("*epsilon*")"),
       y = "Combination Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")
## Warning: Removed 2 rows containing non-finite values (stat_bin).
## Warning: Removed 1 rows containing missing values (geom_bar).

WT heterogenity for Order 4

devs_df_wt %>%
  filter(muts == 4) %>%
  ggplot(aes(x = devs)) +
  geom_histogram(binwidth=0.08, color = "black", lwd = 0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  theme_classic() +
  scale_x_continuous(limits = c(0, 3)) + # Same scale used later
  labs(x = expression("Deviation from Combinatorial Mean ("*epsilon*")"),
       y = "Combination Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")
## Warning: Removed 5 rows containing non-finite values (stat_bin).
## Warning: Removed 1 rows containing missing values (geom_bar).

WT heterogenity for Order 2-4 in facet grid

devs_df_wt_multi = devs_df_wt %>%
  filter(muts == 2 | muts == 3 | muts == 4) %>%
  ggplot(aes(x = devs)) +
  geom_histogram(binwidth=0.1, color = "black", lwd = 0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  facet_grid(~ muts) +
  scale_x_continuous(limits = c(0, 3)) +
  theme_classic() +
  labs(x = expression("Deviation from Combinatorial Mean ("*epsilon*")"),
       y = "Combination Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")

devs_df_wt_multi
## Warning: Removed 8 rows containing non-finite values (stat_bin).
## Warning: Removed 6 rows containing missing values (geom_bar).

#ggsave("fig_2C.svg", devs_df_wt_multi, width = 180, height = 247/4, dpi = 300, units = "mm")

Table to show percentages of WT-bg points that deviate from the positional/combinatorial mean by significance threshold (log10 1.5-fold)

devs_df_wt %>%
  mutate(muts = factor(muts)) %>%
  group_by(muts) %>%
  summarise(percent = sum(devs > log10(1.5)) / length(devs),
            outlier = sum(devs > log10(1.5)),
            total = length(devs)) %>%
  knitr::kable()
muts percent outlier total
1 0.6775701 145 214
2 0.6443914 270 419
3 0.5570776 244 438
4 0.6244898 153 245

Table to show percentages of WT-bg points that deviate from the positional/combinatorial mean by multiple significance threshold (log10 1.5-, 2-, 5-, and 10-fold)

devs_df_wt %>%
  mutate(Order = factor(muts)) %>%
  group_by(Order) %>%
  summarise(percent_1.5 = round(sum(devs > log10(1.5)) / length(devs) *100, 1),
            outlier_1.5 = sum(devs > log10(1.5)),
            percent_2 = round(sum(devs > log10(2)) / length(devs) *100, 1),
            outlier_2 = sum(devs > log10(2)),
            percent_5 = round(sum(devs > log10(5)) / length(devs) *100, 1),
            outlier_5 = sum(devs > log10(5)),
            percent_10 = round(sum(devs > log10(10)) / length(devs) *100, 1), 
            outlier_10 = sum(devs > log10(10)),
            total = length(devs)) %>%
  knitr::kable()
Order percent_1.5 outlier_1.5 percent_2 outlier_2 percent_5 outlier_5 percent_10 outlier_10 total
1 67.8 145 51.4 110 19.6 42 9.8 21 214
2 64.4 270 51.6 216 21.7 91 10.0 42 419
3 55.7 244 34.5 151 18.9 83 13.7 60 438
4 62.4 153 33.9 83 6.9 17 4.9 12 245

All points to Mean Deviation

Purpose of this analysis was to determine the difference in \(\Delta\)Function between functional contribution of a given position/combination in any background and the mean contribution of a given position or combination

Histogram

The spread of all positional contribution vs mean differences for each Order (1-4)

devs = c()
cur_mutations = c()
cur_partial_id = c()
for(i in 1:dim(higher_df_mean)[1]) {
  curr_id = higher_df_mean$unique_id[i]
  devs = c(devs, abs( (higher_df %>% filter(unique_id == curr_id) %>% pull(avg)) - (higher_df_mean$avg[i] ) ))
  cur_mutations = c(cur_mutations, (higher_df %>% filter(unique_id == curr_id) %>% pull(mutations)))
  cur_partial_id = c(cur_partial_id, (higher_df %>% filter(unique_id == curr_id) %>% pull(partial_id)))
}

devs_df = data.frame(devs = devs, muts = cur_mutations, partial_id = cur_partial_id)

All heterogenity for Order 1

devs_df %>%
  filter(muts == 1) %>%
  ggplot(aes(x = devs)) +
  geom_histogram(binwidth=0.08, color = "black", lwd=0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  theme_classic() +
  labs(x = expression("Deviation from Positional Mean ("*Delta*italic("F")*")"),
       y = "Genotype Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")

All heterogenity for Order 2

devs_df %>%
  filter(muts == 2) %>%
  ggplot(aes(x = devs)) +
  geom_histogram(binwidth=0.08, color = "black", lwd=0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  theme_classic() +
  labs(x = expression("Deviation from Positional Mean ("*Delta*italic("F")*")"),
       y = "Genotype Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")

All heterogenity for Order 3

devs_df %>%
  filter(muts == 3) %>%
  ggplot(aes(x = devs)) +
  geom_histogram(binwidth=0.08, color = "black", lwd=0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  theme_classic() +
  labs(x = expression("Deviation from Positional Mean ("*Delta*italic("F")*")"),
       y = "Genotype Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")

All heterogenity for Order 4

devs_df %>%
  filter(muts == 4) %>%
  ggplot(aes(x = devs)) +
  geom_histogram(binwidth=0.08, color = "black", lwd=0.1, fill = "#edae49") +
  geom_vline(xintercept = log10(1.5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(2), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(5), lty = 2, lwd = 0.2) +
  geom_vline(xintercept = log10(10), lty = 2, lwd = 0.2) +
  theme_classic() +
  labs(x = expression("Deviation from Positional Mean ("*Delta*italic("F")*")"),
       y = "Genotype Count") +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none")

Table to show percentages of WT-bg points that deviate from the positional/combinatorial mean by significance threshold (log10 1.5-fold)

devs_df %>%
  mutate(Order = factor(muts)) %>%
  group_by(Order) %>%
  summarise(percent = sum(devs > log10(1.5)) / length(devs),
            outlier = sum(devs > log10(1.5)),
            total = length(devs)) %>%
  knitr::kable()
Order percent outlier total
1 0.5895669 2396 4064
2 0.5278253 2466 4672
3 0.4929435 1467 2976
4 0.5598214 627 1120

Table to show percentages of WT-bg points that deviate from the positional/combinatorial mean by many significance thresholds (log10 1.5-, 2-, 5-, and 10-fold)

devs_df %>%
  mutate(Order = factor(muts)) %>%
  group_by(Order) %>%
  summarise(percent_1.5 = sum(devs > log10(1.5)) / length(devs),
            outlier_1.5 = sum(devs > log10(1.5)),
            percent_2 = sum(devs > log10(2)) / length(devs),
            outlier_2 = sum(devs > log10(2)),
            percent_5 = sum(devs > log10(5)) / length(devs),
            outlier_5 = sum(devs > log10(5)),
            percent_10 = sum(devs > log10(10)) / length(devs),
            outlier_10 = sum(devs > log10(10)),
            total = length(devs)) %>%
  knitr::kable()
Order percent_1.5 outlier_1.5 percent_2 outlier_2 percent_5 outlier_5 percent_10 outlier_10 total
1 0.5895669 2396 0.4050197 1646 0.1478839 601 0.0814469 331 4064
2 0.5278253 2466 0.3488870 1630 0.1335616 624 0.0766267 358 4672
3 0.4929435 1467 0.3067876 913 0.1159274 345 0.0762769 227 2976
4 0.5598214 627 0.3455357 387 0.0901786 101 0.0500000 56 1120

Prediction

all_mae = lapply(paste0("Output/", list.files(path = "Output", pattern="aic_*", recursive = T)), read_csv, skip = 1, show_col_types=F, col_names = c("MAE", "Last MAE", "Step", "Enzyme", "Linear MAE", "Linear Last MAE"))

for(element in 1:length(all_mae)){
  all_mae[[element]]$ID = str_split(list.files(path = "Output", pattern="aic_*", recursive = T)[element], "/")[[1]][1]
}

all_mae = do.call("rbind", all_mae)

Some statistics for the AE for each model. Now F is converted to fold-change in function (but remains WT-normalized)

all_mae %>% 
  group_by(Step) %>% 
  summarise(wtbg_mean = 10^mean(`Last MAE`),
            wtbg_median = 10^median(`Last MAE`),
            lin_mean = 10^mean(`Linear Last MAE`),
            lin_median = 10^median(`Linear Last MAE`)) %>%
  knitr::kable()
Step wtbg_mean wtbg_median lin_mean lin_median
1 20.531688 8.008615 2.945869 2.302982
2 106.163799 63.740988 2.023382 1.765125
3 51.067872 8.952979 1.267406 1.183051
4 19.699102 3.151889 1.108533 1.073554
5 7.322787 1.313971 1.094891 1.080794
6 1.730950 1.000000 1.114261 1.106314
7 1.000000 1.000000 1.087920 1.087920

After loading and assigning ID corresponding to each landscape value (should be 45) we can plot linear and WT-model MAE’s with their constituents

all_mae_long = all_mae %>%
  pivot_longer(cols = c('Last MAE', 'Linear Last MAE'), names_to = "Model", values_to = "AE") %>%
    filter(Step < 5)
  
mae_ggplot = all_mae_long %>%
  ggplot(aes(x = Step, y = AE, color = Model)) +
  geom_point(size = 1, position=position_jitterdodge(jitter.width = 0.1)) +
  stat_summary(data = all_mae_long %>% filter(Model == "Last MAE"), fun=mean, colour="black", geom="crossbar", width=0.2, position = position_nudge(x = -0.19, y = 0), size = 0.3) +
  stat_summary(data = all_mae_long %>% filter(Model == "Linear Last MAE"), fun=mean, colour="black", geom="crossbar", width=0.2, position = position_nudge(x = 0.19, y = 0),size = 0.3) +
   stat_summary(data = all_mae_long %>% filter(Model == "Last MAE"), fun=median, colour="darkred", geom="crossbar", width=0.2, position = position_nudge(x = -0.19, y = 0), size = 0.3) +
  stat_summary(data = all_mae_long %>% filter(Model == "Linear Last MAE"), fun=median, colour="darkred", geom="crossbar", width=0.2, position = position_nudge(x = 0.19, y = 0),size = 0.3) +
  geom_hline(yintercept = log10(1.5), lty = 2, size = 0.2) +
  scale_color_manual(values = c("#edae49", "#4988ed")) +
  labs(x = "Order of the Model", 
       y = expression("Absolute Error of Predicted"*italic(" F"))) +
  theme_classic() +
  theme(axis.line = element_line(size = 0.2, color = "black"), axis.ticks = element_line(size = 0.2, color = "black"), text = element_text(size = 9), axis.text = element_text(size = 8, color = "black"), legend.position = "none") +
  coord_cartesian(ylim=c(0, 6)) # Zoom without affecting means and medians

mae_ggplot

#ggsave("fig_3B.svg", mae_ggplot, width = 180/2, height = 247/4, dpi = 300, units = "mm")

This plot omits some data from being viewed, however plotted meeans and medians are accurate. The figure is eddited outside of the code for technical

What is the distribution of predicted vs non-predicted at each order, not just the means?

all_mae_long %>%
  group_by(Step, Model) %>%
  summarise(pred= length(AE[AE < log10(1.5)]), 
            non_pred= length(AE[AE >= log10(1.5)])) %>%
  mutate(pred_ratio = round(pred/(pred+non_pred)*100,2)) %>%
  knitr::kable()
## `summarise()` has grouped output by 'Step'. You can override using the `.groups` argument.
Step Model pred non_pred pred_ratio
1 Last MAE 6 39 13.33
1 Linear Last MAE 13 32 28.89
2 Last MAE 5 40 11.11
2 Linear Last MAE 15 30 33.33
3 Last MAE 5 40 11.11
3 Linear Last MAE 34 11 75.56
4 Last MAE 4 21 16.00
4 Linear Last MAE 24 1 96.00

Trajectory

Seeing how adaptive trajectories are affected by epistasis

First I defined the adaptive trajectories. These are hardcoded based on the dataset I am working with.

adaptive_trajectories = c("DHFR_ki_trajg", 
                          "DHFR_ki_trajr",
                          "MPH_catact_ZnPTM",
                          "NfsA_ec50_2039",
                          "NfsA_ec50_3637",
                          "OXA-48_ic50_CAZtraj1",
                          "OXA-48_ic50_CAZtraj2",
                          "OXA-48_ic50_CAZtraj3",
                          "PTE_catact_2NH",
                          "TEM_MIC_weinreich",
                          "DHFR_ic75_palmer")

Then I need to create a global trajectory data frame

all_traj = do.call("rbind", lapply(paste0("Output/", list.files(path = "Output", pattern="traj_epi_*", recursive = T)), read_csv, skip = 1, show_col_types=F, col_names = c("genotype", "avg", "pos", "mutations", "likely", "enzyme_name", "measure_type", "cond")))

all_traj = all_traj %>% unite("unique_id", c(enzyme_name, measure_type, cond), remove = F)

Next I need to filter landscapes by whether they are adaptive or not

adaptive_traj = all_traj %>% filter(unique_id %in% adaptive_trajectories)

Which genotypes in the adaptive landscapes for the most accessible trajectory, as defined by the boolean variable likely, are POSITIVELY epistatic and epistatic in general?

Note: some trajectories don’t go to the last variant, so we explore epistasis of all other genotypes which may go beyond last variant

adaptive_traj_favored = adaptive_traj %>% filter(mutations > 1 & likely) %>% pull(avg)

sum(adaptive_traj_favored > log10(1.5)) / length(adaptive_traj_favored)
## [1] 0.3809524
sum(adaptive_traj_favored > log10(1.5) | adaptive_traj_favored < log10(1/1.5)) / length(adaptive_traj_favored)
## [1] 0.6428571

How many positive epistatic vs all epistatic genotypes vs all genotypes encountered in these landscapes?

sum(adaptive_traj_favored > log10(1.5))
## [1] 16
sum(adaptive_traj_favored > log10(1.5) | adaptive_traj_favored < log10(1/1.5))
## [1] 27
length(adaptive_traj_favored)
## [1] 42

Which genotypes in the non-adaptive landscapes for the favored trajectory are NEGATIVELY epistatic and epistatic in general? Also total genotypes that are not most accessible, with percentages of negative epistasis and epistasis in general.

`%notin%` <- Negate(`%in%`)

non_adaptive_traj_favored = all_traj %>% filter(unique_id %notin% adaptive_trajectories & mutations > 1 & !likely) %>% pull(avg)

sum(non_adaptive_traj_favored < log10(1/1.5))
## [1] 204
sum(non_adaptive_traj_favored > log10(1.5) | non_adaptive_traj_favored < log10(1/1.5))
## [1] 408
length(non_adaptive_traj_favored)
## [1] 557
sum(non_adaptive_traj_favored < log10(1/1.5)) / length(non_adaptive_traj_favored)
## [1] 0.3662478
sum(non_adaptive_traj_favored > log10(1.5) | non_adaptive_traj_favored < log10(1/1.5)) / length(non_adaptive_traj_favored)
## [1] 0.7324955

Prediction of relevant trajectories

We construct thee plotting_d tibble which has information about the observed effect, linear model effect which is simply ccalled epistatic effect and the effect of each order of the WT-background model

adaptive_traj_fave = adaptive_traj %>% filter(likely)

###

plotting_d = tibble()
dummy2 = data.frame()

for(i in 1:length(adaptive_trajectories)) {
  
  suffix = tail(str_split(adaptive_trajectories[i], "_")[[1]], 1)
  
  file = paste0("pred_df_", suffix, "_", adaptive_trajectories[i], ".csv")
  
  d = read_csv(paste0("Output/", adaptive_trajectories[i], "/", file), show_col_types=F)
  
  genos = str_replace_all(adaptive_traj_fave[which(adaptive_traj_fave$unique_id %in% adaptive_trajectories[i]),]$genotype, "x", "1")
  
  genos = c(str_replace_all(genos[1], "1", "0"), genos)
  
  dummy2 = rbind(dummy2, data.frame(trajectory = adaptive_trajectories[i], Z = d[which(d$numbers == tail(genos, 1)),]$`observed effect`))
  
  others = c()
  for(j in 1:(length(genos) - 2)) {
    others = c(others, colnames(d)[which(colnames(d) == "mutations") + j]) ## Get all steps before final step of evaluated genotype
  }
  
  plotting_d = rbind(plotting_d, d[which(d$numbers %in% genos),] %>%
    pivot_longer(cols = c(`observed effect`,
                          `epistatic effect`,
                          `WT effect`,
                          others)) %>% ## add those steps into line plots
    select(c(mutations, name, value)) %>%
    mutate(trajectory = adaptive_trajectories[i]))

}

Next we plot all of those

ggplot(plotting_d, aes(x = mutations, y = value, color = name)) +
  geom_line(lwd = 2) +
  facet_wrap(~ trajectory) +
  geom_hline(data = dummy2, aes(yintercept = Z)) +
  geom_hline(data = dummy2, aes(yintercept = Z + log10(1.5)), lty = 2) +
  geom_hline(data = dummy2, aes(yintercept = Z - log10(1.5)), lty = 2) +
  geom_hline(data = dummy2, aes(yintercept = Z + log10(10)), lty = 2, color = "grey") +
  geom_hline(data = dummy2, aes(yintercept = Z - log10(10)), lty = 2, color = "grey") +
  theme_classic()

Also return as a table

plotting_d %>%
  pivot_wider(names_from = name, values_from = value) %>%
  knitr::kable()
mutations trajectory observed effect epistatic effect WT effect 2 step 3 step 4 step final step 5 step 6 step
0 DHFR_ki_trajg 0.0000000 -0.0124266 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 NA NA
1 DHFR_ki_trajg 1.1303338 1.1421598 1.1303338 1.1303338 1.1303338 1.1303338 1.1303338 NA NA
2 DHFR_ki_trajg 2.3598355 2.3480971 1.7504698 2.3598355 2.3598355 2.3598355 2.3598355 NA NA
3 DHFR_ki_trajg 3.3541084 3.3664861 2.0928925 3.3782593 3.3541084 3.3541084 3.3541084 NA NA
4 DHFR_ki_trajg 4.5820634 4.5691010 2.4392455 6.4837389 4.2208458 4.5820634 4.5820634 NA NA
5 DHFR_ki_trajg 5.9656720 5.9782807 2.7914280 9.0023947 3.9479878 6.3680742 5.9656720 NA NA
0 DHFR_ki_trajr 0.0000000 -0.0155046 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 NA NA
1 DHFR_ki_trajr 1.1303338 1.1452378 1.1303338 1.1303338 1.1303338 1.1303338 1.1303338 NA NA
2 DHFR_ki_trajr 2.3598355 2.3450191 1.7504698 2.3598355 2.3598355 2.3598355 2.3598355 NA NA
3 DHFR_ki_trajr 3.3541084 3.3695641 2.0928925 3.3782593 3.3541084 3.3541084 3.3541084 NA NA
4 DHFR_ki_trajr 4.2810334 4.2664918 2.4450750 5.1111507 4.4545256 4.2810334 4.2810334 NA NA
5 DHFR_ki_trajr 5.2304489 5.2453065 2.8049105 7.8594519 4.0646531 5.7290199 5.2304489 NA NA
0 MPH_catact_ZnPTM 0.0000000 -0.0016066 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 NA NA
1 MPH_catact_ZnPTM 0.9943172 0.9914272 0.9943172 0.9943172 0.9943172 0.9943172 0.9943172 NA NA
2 MPH_catact_ZnPTM 1.2068259 1.2012842 1.2661588 1.2068259 1.2068259 1.2068259 1.2068259 NA NA
3 MPH_catact_ZnPTM 1.2405492 1.2353742 1.9345447 1.2404054 1.2405492 1.2405492 1.2405492 NA NA
4 MPH_catact_ZnPTM 2.3117539 2.3103613 2.8654937 0.4136588 2.0807635 2.3117539 2.3117539 NA NA
5 MPH_catact_ZnPTM 2.9609462 2.9605514 2.0776813 -0.4173805 2.1149224 3.6596868 2.9609462 NA NA
0 NfsA_ec50_2039 0.0000000 -0.0052604 0.0000000 0.0000000 0.0000000 0.0000000 NA 0.0000000 NA
1 NfsA_ec50_2039 0.4216039 0.4174507 0.4216039 0.4216039 0.4216039 0.4216039 NA 0.4216039 NA
2 NfsA_ec50_2039 0.6190933 0.6108143 0.4785088 0.6190933 0.6190933 0.6190933 NA 0.6190933 NA
3 NfsA_ec50_2039 0.7450748 0.7388571 0.4244695 0.7362056 0.7450748 0.7450748 NA 0.7450748 NA
4 NfsA_ec50_2039 0.8488047 0.8477300 0.4121357 0.7618568 0.7740661 0.8488047 NA 0.8488047 NA
5 NfsA_ec50_2039 0.9845273 0.9797227 0.3801515 -0.1849312 1.2563700 1.2151156 NA 0.9845273 NA
0 NfsA_ec50_3637 0.0000000 -0.0052604 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
1 NfsA_ec50_3637 0.4800069 0.4741952 0.4800069 0.4800069 0.4800069 0.4800069 0.4800069 0.4800069 0.4800069
2 NfsA_ec50_3637 0.6711728 0.6693158 0.5369118 0.6711728 0.6711728 0.6711728 0.6711728 0.6711728 0.6711728
3 NfsA_ec50_3637 0.8413595 0.8383239 0.5245781 0.6711856 0.8413595 0.8413595 0.8413595 0.8413595 0.8413595
4 NfsA_ec50_3637 0.9180303 0.9137495 0.4462645 0.4576674 1.4626969 0.9180303 0.9180303 0.9180303 0.9180303
5 NfsA_ec50_3637 0.9566486 0.9519493 0.1443651 0.8355329 1.8320479 0.0426191 0.9566486 0.9566486 0.9566486
6 NfsA_ec50_3637 0.9454686 0.9436716 0.0727609 0.6151170 2.4772843 -0.4757923 0.9454686 1.6847688 0.9454686
7 NfsA_ec50_3637 1.0043214 1.0028427 0.0939502 1.2003309 1.7113959 -1.2265483 1.0043214 4.5060330 -0.9087341
0 OXA-48_ic50_CAZtraj1 0.0000000 -0.0026570 0.0000000 0.0000000 0.0000000 NA 0.0000000 NA NA
1 OXA-48_ic50_CAZtraj1 0.3560259 0.3488146 0.3560259 0.3560259 0.3560259 NA 0.3560259 NA NA
2 OXA-48_ic50_CAZtraj1 1.1398791 1.1223656 0.3360292 1.1398791 1.1398791 NA 1.1398791 NA NA
3 OXA-48_ic50_CAZtraj1 1.4842998 1.4833406 0.4115762 2.0345134 1.4842998 NA 1.4842998 NA NA
4 OXA-48_ic50_CAZtraj1 1.6042261 1.5994638 0.5255195 1.9259530 1.3318026 NA 1.6042261 NA NA
0 OXA-48_ic50_CAZtraj2 0.0000000 -0.0026570 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 NA
1 OXA-48_ic50_CAZtraj2 0.3856063 0.3839493 0.3856063 0.3856063 0.3856063 0.3856063 0.3856063 0.3856063 NA
2 OXA-48_ic50_CAZtraj2 0.8027737 0.7969589 0.7694216 0.8027737 0.8027737 0.8027737 0.8027737 0.8027737 NA
3 OXA-48_ic50_CAZtraj2 1.0934217 1.0916060 0.9093007 1.4373797 1.0934217 1.0934217 1.0934217 1.0934217 NA
4 OXA-48_ic50_CAZtraj2 1.5276299 1.5256020 0.9005268 2.1488613 1.1459227 1.5276299 1.5276299 1.5276299 NA
5 OXA-48_ic50_CAZtraj2 1.5682017 1.5672424 0.8881931 2.2688061 1.6984605 1.6998067 1.5682017 1.5682017 NA
6 OXA-48_ic50_CAZtraj2 1.5078559 1.5046215 0.8967932 1.9530868 0.7115869 2.2277266 1.5078559 1.2706843 NA
0 OXA-48_ic50_CAZtraj3 0.0000000 -0.0026570 0.0000000 0.0000000 0.0000000 0.0000000 NA NA NA
1 OXA-48_ic50_CAZtraj3 0.4329693 0.4292205 0.4329693 0.4329693 0.4329693 0.4329693 NA NA NA
2 OXA-48_ic50_CAZtraj3 0.9938769 0.9737267 0.4898741 0.9938769 0.9938769 0.9938769 NA NA NA
3 OXA-48_ic50_CAZtraj3 1.3364597 1.3340956 0.4941955 1.1216466 1.3364597 1.3364597 NA NA NA
4 OXA-48_ic50_CAZtraj3 1.4149733 1.4081219 0.5355882 0.9184096 1.6022940 1.4149733 NA NA NA
0 PTE_catact_2NH 0.0000000 -0.0030856 0.0000000 0.0000000 0.0000000 0.0000000 NA NA NA
1 PTE_catact_2NH 1.4199557 1.4175792 1.4199557 1.4199557 1.4199557 1.4199557 NA NA NA
2 PTE_catact_2NH 2.2095150 2.2072984 2.2408137 2.2095150 2.2095150 2.2095150 NA NA NA
3 PTE_catact_2NH 3.0211893 3.0194333 2.8546556 4.0243530 3.0211893 3.0211893 NA NA NA
4 PTE_catact_2NH 3.2405492 3.2383995 2.6608355 4.1859390 2.3618565 3.2405492 NA NA NA
0 TEM_MIC_weinreich 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 NA NA
1 TEM_MIC_weinreich 1.2013971 1.2016454 1.2013971 1.2013971 1.2013971 1.2013971 1.2013971 NA NA
2 TEM_MIC_weinreich 3.6117233 3.6118198 1.3803741 3.6117233 3.6117233 3.6117233 3.6117233 NA NA
3 TEM_MIC_weinreich 4.3783979 4.3777366 1.3803741 5.8493869 4.3783979 4.3783979 4.3783979 NA NA
4 TEM_MIC_weinreich 4.5185139 4.5179153 1.2893949 8.6829825 2.5918364 4.5185139 4.5185139 NA NA
5 TEM_MIC_weinreich 4.6683859 4.6683012 1.2893949 8.9067386 3.4005435 4.3989125 4.6683859 NA NA
0 DHFR_ic75_palmer 0.0000000 -0.0177247 0.0000000 0.0000000 0.0000000 NA NA NA NA
1 DHFR_ic75_palmer 1.8555192 1.8548586 1.8555192 1.8555192 1.8555192 NA NA NA NA
2 DHFR_ic75_palmer 2.1931246 2.1911919 2.1630152 2.1931246 2.1931246 NA NA NA NA
3 DHFR_ic75_palmer 2.3424227 2.3418586 2.8064679 2.4667779 2.3424227 NA NA NA NA

Ruggedness plots

I can make a ruggedness plot for each adaptive landscape, where deviation from 0 implies epistatic contribution of that genotype

adaptive_traj %>% 
  filter(mutations > 1 & likely) %>%
  ggplot(aes(x = mutations, y = avg)) +
  geom_line() +
  geom_text_repel(aes(label = genotype), force = 1.5, direction = "y", box.padding = 0, segment.size = 0.2, size = 2.5) +
  geom_hline(yintercept = log10(1.5), lty = 2) +
  geom_hline(yintercept = log10(1/1.5), lty = 2) +
  geom_hline(yintercept = 0) +
  facet_wrap(~ unique_id) +
  theme_classic()

What if we compare it to the mean at that combination or position as well, not just assumed additivity (0 +/- log10(1.5))?

higher_means = higher_df %>%
  unite("partial_id", c(Enzyme, Measurement, Condition), remove = F) %>%
  filter(partial_id %in% adaptive_trajectories) %>% ## use partial ID to only pick up the adaptive trajectories
  group_by(unique_id) %>%
  mutate(avg = mean(avg)) %>% ## Is arithmetic mean OK here?
  ungroup() %>%
  distinct(unique_id, .keep_all = T) ## Remove unique_id replicates

adaptive_means = higher_means %>% arrange(partial_id, pos) %>% pull(avg)

adaptive_traj = adaptive_traj %>% arrange(unique_id, pos) %>% mutate(means = adaptive_means)

Then we make the plot

trajectory_labeller = function(variable,value){
  return(trajectory_names[value])
}

trajectory_names = list(
  "DHFR_ic75_palmer" = expression("DHFR Palmer"*italic(" et al.")),
  "DHFR_ki_trajg" = expression("DHFR Traj. G"),
  "DHFR_ki_trajr" = expression("DHFR Traj. R"),
  "MPH_catact_ZnPTM" = expression("MPH Traj. Zn"),
  "NfsA_ec50_2039" = expression("NfsA Traj. 20_39"),
  "NfsA_ec50_3637" = expression("NfsA Traj. 36_37"),
  "OXA-48_ic50_CAZtraj1" = expression("OXA-48 CAZ Traj. 1"),
  "OXA-48_ic50_CAZtraj2" = expression("OXA-48 CAZ Traj. 2"),
  "OXA-48_ic50_CAZtraj3" = expression("OXA-48 CAZ Traj. 3"),
  "PTE_catact_2NH" = expression("PTE Traj. 2NH"),
  "TEM_MIC_weinreich" = expression("TEM Weinreich"*italic(" et al."))
)

adaptive_traj_plot = adaptive_traj %>%
  filter(likely & mutations > 1) %>%
  mutate(wt_bg = avg) %>%
  pivot_longer(c(wt_bg, means)) %>%
  ggplot(aes(x = factor(mutations), y = value, fill = name)) +
  geom_bar(stat = "identity", position = position_dodge()) +
  #geom_text_repel(aes(label = genotype), force = 1.5, direction = "y", box.padding = 0, segment.size = 0.2, size = 2.5) +
  geom_hline(yintercept = log10(1.5), lty = 2, size = 0.2) +
  geom_hline(yintercept = log10(1/1.5), lty = 2, size = 0.2) +
  geom_hline(yintercept = 0) +
    scale_color_manual(values = c("#edae49", "#4988ed")) +
  facet_wrap(~ unique_id, 
             scales = "free",
             labeller = trajectory_labeller) +
  labs(x = "Mutational Step", 
       y = expression(epsilon)) +
  theme_classic() +
  theme(text = element_text(size=9), axis.text = element_text(size=8, color = "black"),
        legend.position = "none", axis.line=element_line()) +
  scale_fill_manual(values = c("#4988ed", "#edae49")) +
  scale_y_continuous(limits=c(-3,3))
## Warning: The labeller API has been updated. Labellers taking `variable` and
## `value` arguments are now deprecated. See labellers documentation.
adaptive_traj_plot

#ggsave("fig_4.svg", adaptive_traj_plot, width = 180, height = 247/2, dpi = 300, units = "mm")

Which one of the genotypes seen above are the outliers?

adaptive_traj %>%
  filter(likely & mutations > 1) %>%
  mutate(outlier = abs(means - avg) > log10(1.5)) %>%
  select(c(genotype, unique_id)) %>%
  knitr::kable()
genotype unique_id
x0xx00 DHFR_ic75_palmer
00xx00 DHFR_ic75_palmer
xxxxx DHFR_ki_trajg
0xxxx DHFR_ki_trajg
0xx0x DHFR_ki_trajg
00x0x DHFR_ki_trajg
xxxxx DHFR_ki_trajr
xxx0x DHFR_ki_trajr
0xx0x DHFR_ki_trajr
00x0x DHFR_ki_trajr
0xx00 MPH_catact_ZnPTM
0xx0x MPH_catact_ZnPTM
xxxxx MPH_catact_ZnPTM
xxx0x MPH_catact_ZnPTM
xxx00xx NfsA_ec50_2039
x0x00xx NfsA_ec50_2039
x0000x0 NfsA_ec50_2039
x0000xx NfsA_ec50_2039
xxxxxxx NfsA_ec50_3637
xxx0xxx NfsA_ec50_3637
x0x0xxx NfsA_ec50_3637
x0x00x0 NfsA_ec50_3637
x0x00xx NfsA_ec50_3637
x0000x0 NfsA_ec50_3637
xxxx OXA-48_ic50_CAZtraj1
0xxx OXA-48_ic50_CAZtraj1
0x0x OXA-48_ic50_CAZtraj1
00x0x0 OXA-48_ic50_CAZtraj2
00x0xx OXA-48_ic50_CAZtraj2
xxxxxx OXA-48_ic50_CAZtraj2
0xxxxx OXA-48_ic50_CAZtraj2
0xx0xx OXA-48_ic50_CAZtraj2
xx0x00 OXA-48_ic50_CAZtraj3
xx0x0x OXA-48_ic50_CAZtraj3
x00x00 OXA-48_ic50_CAZtraj3
xxx0x0 PTE_catact_2NH
xx00x0 PTE_catact_2NH
0x00x0 PTE_catact_2NH
00x0x TEM_MIC_weinreich
0xxxx TEM_MIC_weinreich
0xx0x TEM_MIC_weinreich
xxxxx TEM_MIC_weinreich

Now we swich gears to look at the entire adaptive landscapes, not just the most accessible trajectory.

What % of adaptive landscape genotypes are outliers from the mean? What % of adaptive accessible trajectory genotypes are outliers from the mean? What % of adaptive less accessible trajectory genotypes are outliers from the mean?

adaptive_traj_final = adaptive_traj %>%
  mutate(outlier = abs(means - avg) > log10(1.5))

length(adaptive_traj_final$outlier)
## [1] 645
sum(adaptive_traj_final$outlier)
## [1] 309
sum(adaptive_traj_final$outlier) / length(adaptive_traj_final$outlier)
## [1] 0.4790698
length(filter(adaptive_traj_final, likely) %>% pull(outlier))
## [1] 53
sum(filter(adaptive_traj_final, likely) %>% pull(outlier))
## [1] 30
sum(filter(adaptive_traj_final, likely) %>% pull(outlier)) / length(filter(adaptive_traj_final, likely) %>% pull(outlier))
## [1] 0.5660377
length(filter(adaptive_traj_final, !likely) %>% pull(outlier))
## [1] 592
sum(filter(adaptive_traj_final, !likely) %>% pull(outlier))
## [1] 279
sum(filter(adaptive_traj_final, !likely) %>% pull(outlier)) / length(filter(adaptive_traj_final, !likely) %>% pull(outlier))
## [1] 0.4712838

Diminishing Returns

Next we try to see if adaptive vs random trajectories show diminishing returns.

Doing for single mutants first for every single landscape…

higher_df_diminish = higher_df %>%
  unite("partial_id", c(Enzyme, Measurement, Condition)) %>%
  filter(mutations == 1) %>%
  mutate(from = str_replace_all(genotype, "x", "0"),
         to = str_replace_all(genotype, "x", "1"))

start_effect = c()
for(i in 1:dim(higher_df_diminish)[1]) {
  
  if(!str_detect(higher_df_diminish$from[i], "1")) {
    start_effect = c(start_effect, 0) # If starts from WT, start effect is 0
  } else {
    start_effect = c(start_effect, filter(fit_land, unique_id == higher_df_diminish$partial_id[i] & id == higher_df_diminish$from[i]) 
  %>% pull(effect))
  }
}

higher_df_diminish$start_effect = start_effect

ggplot(higher_df_diminish, aes(x = start_effect, y = avg)) +
  geom_point() +
  theme_classic()

Next only looking at adaptive landscapes

higher_df_diminish = higher_df %>%
  unite("partial_id", c(Enzyme, Measurement, Condition)) %>%
  filter(mutations == 1) %>%
  mutate(from = str_replace_all(genotype, "x", "0"),
         to = str_replace_all(genotype, "x", "1")) %>%
  filter(partial_id %in% adaptive_trajectories)

start_effect = c()
for(i in 1:dim(higher_df_diminish)[1]) {
  
  if(!str_detect(higher_df_diminish$from[i], "1")) {
    start_effect = c(start_effect, 0) # If starts from WT, start effect is 0
  } else {
    start_effect = c(start_effect, filter(fit_land, unique_id == higher_df_diminish$partial_id[i] & id == higher_df_diminish$from[i]) 
  %>% pull(effect))
  }
}

higher_df_diminish$start_effect = start_effect

ggplot(higher_df_diminish, aes(x = start_effect, y = avg)) +
  geom_point() +
  facet_wrap(~ partial_id) +
  geom_smooth(method = 'lm', formula = y ~ x) +
  stat_cor(aes(label = paste(..rr.label.., ..p.label.., sep = "~~")), color = "red", geom = "label", label.x = -2.5, label.y = 4, r.accuracy = 0.01, p.accuracy = 0.01) +
  theme_classic()

What about only looking at the best step from each starting genotype?

higher_df_diminish %>%
  group_by(partial_id, from) %>%
  summarise(avg = max(avg), start_effect = start_effect) %>%
  distinct() %>%
  ggplot(aes(x = start_effect, y = avg)) +
  geom_point() +
  geom_smooth(method = 'lm', formula = y ~ x) +
  stat_cor(aes(label = paste(..rr.label.., ..p.label.., sep = "~~")), color = "red", geom = "label", label.x = -2, label.y = 4.7, r.accuracy = 0.01, p.accuracy = 0.01) +
  facet_wrap(~ partial_id) +
  theme_classic()
## `summarise()` has grouped output by 'partial_id', 'from'. You can override using the `.groups` argument.

What about only looking at the adaptive trajectories?

all_traj_points = all_traj %>% 
  filter(likely & unique_id %in% adaptive_trajectories) %>%
  mutate(genotype = str_replace_all(genotype, "x", "1")) %>%
  select(genotype, unique_id)


higher_df_diminish_traj = tibble()
prev_geno = c()
for(i in 1:dim(all_traj_points)[1]) {
 
  if(length(prev_geno) > 0) {
    higher_df_diminish_traj = rbind(higher_df_diminish_traj, higher_df_diminish %>% filter(partial_id == all_traj_points$unique_id[i] & to == all_traj_points$genotype[i]) %>% filter(from == prev_geno)) 
  } else {
    higher_df_diminish_traj = rbind(higher_df_diminish_traj, higher_df_diminish %>% filter(partial_id == all_traj_points$unique_id[i] & to == all_traj_points$genotype[i]))
  }
    
  if(i != dim(all_traj_points)[1]) { 
    if(all_traj_points$unique_id[i + 1] == all_traj_points$unique_id[i]) {
      prev_geno = tail(higher_df_diminish_traj$to, 1)
    } else {
      prev_geno = c()
    }
  }

}

higher_df_diminish_traj %>%
  ggplot(aes(x = start_effect, y = avg)) +
  geom_point() +
  geom_smooth(method = 'lm', formula = y ~ x) +
  stat_cor(aes(label = paste(..rr.label.., ..p.label.., sep = "~~")), color = "red", geom = "label", label.x = 0, label.y = 3.7, r.accuracy = 0.01, p.accuracy = 0.01) +
  facet_wrap(~ partial_id) +
  theme_classic()

We can also do a side by side correlation comparison of starting effect vs MAXIMUM delFs as well as vs ALL POSSIBLE delFs

max_list = higher_df_diminish %>%
  group_by(partial_id, from) %>%
  summarise(avg = max(avg), start_effect = start_effect) %>%
  distinct()
## `summarise()` has grouped output by 'partial_id', 'from'. You can override using the `.groups` argument.
maxes = c()
for(entry in 1:dim(higher_df_diminish)[1]) {
  maxes = c(maxes, ifelse(any(higher_df_diminish[entry,]$from == max_list$from & higher_df_diminish[entry,]$partial_id == max_list$partial_id & higher_df_diminish[entry,]$avg == max_list$avg & higher_df_diminish[entry,]$start_effect == max_list$start_effect), T, F))
}

higher_df_diminish$is_max = maxes

higher_df_diminish_plot = higher_df_diminish %>%
  ggplot(aes(x = start_effect, y = avg)) +
  geom_point(aes(fill = is_max), shape = 21, color = "black", stroke = 0.1) +
  geom_smooth(method = 'lm', formula = y ~ x, color = "grey") +
  geom_smooth(data = higher_df_diminish %>% filter(is_max), method = 'lm', formula = y ~ x, color = "#edae49") +
  stat_cor(aes(label = paste(..rr.label.., sep = "~~")), label.x = 2, label.y = 5.5, r.accuracy = 0.01, size = 2.5, color = "grey") +
  stat_cor(data = higher_df_diminish %>% filter(is_max), aes(label = paste(..rr.label.., sep = "~~")), label.x = 2, label.y = 4, r.accuracy = 0.01, size = 2.5, color = "#edae49") +
  facet_wrap(~ partial_id, scales = "free") +
  labs(x = expression("Starting Function ("*italic("F")*")"), 
       y = expression(Delta*'F')) +
  theme_classic() +
  theme(text = element_text(size=9), axis.text = element_text(size=8, color = "black"),
        legend.position = "none", axis.line=element_line()) +
  scale_fill_manual(values = c("grey", "#edae49")) +
  scale_x_continuous(limits=c(-6,6)) + 
  scale_y_continuous(limits=c(-6,6))

higher_df_diminish_plot

#ggsave("supp_fig_3.svg", higher_df_diminish_plot, width = 180, height = 247/2, dpi = 300, units = "mm")

Other Exploratory Work

Modify adaptive traj to also have the genotypic effect from fit_land. To do this I need to take the unique_id from adaptive traj and the genotype after x -> 1 modification from adaptive traj, and find the corresponding value of the genotype in fit_land

traj_effects = c()
for(i in 1:dim(adaptive_traj)[1]){
  
  traj_effects= c(traj_effects, fit_land %>%
    filter(unique_id == adaptive_traj$unique_id[i]) %>%
    filter(id == str_replace_all(adaptive_traj$genotype[i], "x", "1")) %>%
    pull(effect))
  
}

adaptive_traj$traj_effects = traj_effects

Now that adaptive_traj has genotype effects, we can ask the question: Did the idiosyncratic epistasis at that order specifically enable or restrict that genotype.

access = c()
access_no_idio = c()
access_mean = c()

for(i in 1:dim(adaptive_traj)[1]) {
  
  current_test = adaptive_traj[i,]
  
  if(current_test$mutations != 1) {
    loc = str_locate_all(current_test$genotype, "x")[[1]][,1]
    len = str_length(current_test$genotype)
    
    func = c()
    
    # Get all previous constituents
    for(j in 1:length(loc)) {
      const = current_test$genotype
      substr(const, loc[j], loc[j]) = "0"
      
      func = c(func, adaptive_traj %>% filter(unique_id == current_test$unique_id & genotype == const) %>% pull(traj_effects))
    }
  
    access = c(access, sum(current_test$traj_effects - func >= 0))
    access_no_idio = c(access_no_idio, sum((current_test$traj_effects - current_test$avg) - func >= 0)) # Access without epistasis
    access_mean = c(access_mean, sum((current_test$traj_effects - (current_test$avg - current_test$means)) - func >= 0))
  } else {
    access = c(access, NA)
    access_no_idio = c(access_no_idio, NA)
    access_mean = c(access_mean, NA)
  }
}

Now let’s look at the accessibility metrics in a tibble

access_df = tibble(access = access,
                   access_no_idio = access_no_idio,
                   access_mean = access_mean)

access_df = access_df %>% mutate(access_w_mean = access_mean - access,
                     access_w_idio = access - access_no_idio)

adaptive_traj_access = cbind(adaptive_traj, access_df)

adaptive_traj_access
##     genotype           avg                               pos mutations likely
## 1     x00000  0.6434526765                                p1         1  FALSE
## 2     xx0000  0.0120089075                            p1|p21         2  FALSE
## 3     xxx000  4.0915005511                        p1|p21|p26         3  FALSE
## 4     xxxx00 -3.4400739596                    p1|p21|p26|p28         4  FALSE
## 5     xxxxx0  0.2127319126                p1|p21|p26|p28|p30         5  FALSE
## 6     xxxxxx -7.1891355892            p1|p21|p26|p28|p30|p94         6  FALSE
## 7     xxxx0x 10.4358637805                p1|p21|p26|p28|p94         5  FALSE
## 8     xxx0x0 -3.8204466134                    p1|p21|p26|p30         4  FALSE
## 9     xxx0xx  2.5755327809                p1|p21|p26|p30|p94         5  FALSE
## 10    xxx00x -5.3028285005                    p1|p21|p26|p94         4  FALSE
## 11    xx0x00  0.7938783708                        p1|p21|p28         3  FALSE
## 12    xx0xx0  1.9958051082                    p1|p21|p28|p30         4  FALSE
## 13    xx0xxx  3.1289862437                p1|p21|p28|p30|p94         5  FALSE
## 14    xx0x0x -5.2140863284                    p1|p21|p28|p94         4  FALSE
## 15    xx00x0 -0.3089210603                        p1|p21|p30         3  FALSE
## 16    xx00xx  1.3698610227                    p1|p21|p30|p94         4  FALSE
## 17    xx000x  1.0635937667                        p1|p21|p94         3  FALSE
## 18    x0x000  0.1951793213                            p1|p26         2  FALSE
## 19    x0xx00 -0.1243552470                        p1|p26|p28         3   TRUE
## 20    x0xxx0  0.2566376927                    p1|p26|p28|p30         4  FALSE
## 21    x0xxxx  0.5135760858                p1|p26|p28|p30|p94         5  FALSE
## 22    x0xx0x -1.1042304716                    p1|p26|p28|p94         4  FALSE
## 23    x0x0x0 -0.5804441706                        p1|p26|p30         3  FALSE
## 24    x0x0xx  0.2071172162                    p1|p26|p30|p94         4  FALSE
## 25    x0x00x  0.7200699261                        p1|p26|p94         3  FALSE
## 26    x00x00 -0.5649786683                            p1|p28         2  FALSE
## 27    x00xx0 -0.3853196942                        p1|p28|p30         3  FALSE
## 28    x00xxx  2.2307063095                    p1|p28|p30|p94         4  FALSE
## 29    x00x0x  1.0706822252                        p1|p28|p94         3  FALSE
## 30    x000x0  0.8028661382                            p1|p30         2  FALSE
## 31    x000xx -0.7695624415                        p1|p30|p94         3  FALSE
## 32    x0000x -0.5587019239                            p1|p94         2  FALSE
## 33    0x0000  0.7283537820                               p21         1  FALSE
## 34    0xx000 -4.0673668714                           p21|p26         2  FALSE
## 35    0xxx00  3.2599112109                       p21|p26|p28         3  FALSE
## 36    0xxxx0 -0.1092526217                   p21|p26|p28|p30         4  FALSE
## 37    0xxxxx  0.9545832341               p21|p26|p28|p30|p94         5  FALSE
## 38    0xxx0x -4.7257531982                   p21|p26|p28|p94         4  FALSE
## 39    0xx0x0  3.7900356730                       p21|p26|p30         3  FALSE
## 40    0xx0xx -1.8299171248                   p21|p26|p30|p94         4  FALSE
## 41    0xx00x  5.0316956326                       p21|p26|p94         3  FALSE
## 42    0x0x00 -1.3963522169                           p21|p28         2  FALSE
## 43    0x0xx0 -1.6714200186                       p21|p28|p30         3  FALSE
## 44    0x0xxx  2.6259368082                   p21|p28|p30|p94         4  FALSE
## 45    0x0x0x  0.0760740241                       p21|p28|p94         3  FALSE
## 46    0x00x0 -0.2888077281                           p21|p30         2  FALSE
## 47    0x00xx -1.5696223558                       p21|p30|p94         3  FALSE
## 48    0x000x -1.3782885860                           p21|p94         2  FALSE
## 49    00x000  0.3074960379                               p26         1  FALSE
## 50    00xx00  0.0301094048                           p26|p28         2   TRUE
## 51    00xxx0 -0.5331881295                       p26|p28|p30         3  FALSE
## 52    00xxxx  0.0894805599                   p26|p28|p30|p94         4  FALSE
## 53    00xx0x  0.7498001253                       p26|p28|p94         3  FALSE
## 54    00x0x0  0.4506380989                           p26|p30         2  FALSE
## 55    00x0xx -0.4343233914                       p26|p30|p94         3  FALSE
## 56    00x00x -0.7310344646                           p26|p94         2  FALSE
## 57    000x00  1.8555191557                               p28         1   TRUE
## 58    000xx0 -0.2985650502                           p28|p30         2  FALSE
## 59    000xxx -2.0436471012                       p28|p30|p94         3  FALSE
## 60    000x0x -1.6354286857                           p28|p94         2  FALSE
## 61    0000x0  0.2671717284                               p30         1  FALSE
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## 607   00x00x  0.0648224329                         p271|p313         2  FALSE
## 608   000x00  0.2741578493                              p272         1  FALSE
## 609   000xx0 -0.3267576767                         p272|p306         2  FALSE
## 610   000xxx  0.3574692657                    p272|p306|p313         3  FALSE
## 611   000x0x  0.1624115618                         p272|p313         2  FALSE
## 612   0000x0  1.4199557485                              p306         1   TRUE
## 613   0000xx -0.6633727076                         p306|p313         2  FALSE
## 614   00000x -0.0655015488                              p313         1  FALSE
## 615    00x00  0.1789769473                              p104         1  FALSE
## 616    00xx0  0.1815151427                         p104|p182         2  FALSE
## 617    00xxx -1.5412194020                    p104|p182|p238         3  FALSE
## 618    00x0x  2.2313492364                         p104|p238         2   TRUE
## 619    000x0 -0.0909791458                              p182         1  FALSE
## 620    000xx  1.4506834051                         p182|p238         2  FALSE
## 621    0000x  1.2013971243                              p238         1   TRUE
## 622    0x000  0.0000000000                               p42         1  FALSE
## 623    0xx00  1.0224201770                          p42|p104         2  FALSE
## 624    0xxx0 -1.6219400557                     p42|p104|p182         3  FALSE
## 625    0xxxx  1.9266775533                p42|p104|p182|p238         4   TRUE
## 626    0xx0x -1.4709889671                     p42|p104|p238         3   TRUE
## 627    0x0x0  1.2923762701                          p42|p182         2  FALSE
## 628    0x0xx -1.4569977288                     p42|p182|p238         3  FALSE
## 629    0x00x  1.2152433830                          p42|p238         2  FALSE
## 630    x0000  0.0000000000                             p4205         1  FALSE
## 631    x0x00  0.1327769138                        p4205|p104         2  FALSE
## 632    x0xx0 -0.1815151427                   p4205|p104|p182         3  FALSE
## 633    x0xxx -0.1024321887              p4205|p104|p182|p238         4  FALSE
## 634    x0x0x -0.1327769138                   p4205|p104|p238         3  FALSE
## 635    x00x0  0.0909791458                        p4205|p182         2  FALSE
## 636    x00xx  0.9596427786                   p4205|p182|p238         3  FALSE
## 637    x000x  0.0000000000                        p4205|p238         2  FALSE
## 638    xx000  0.0000000000                         p4205|p42         2  FALSE
## 639    xxx00  0.0368938242                    p4205|p42|p104         3  FALSE
## 640    xxxx0  1.4522693177               p4205|p42|p104|p182         4  FALSE
## 641    xxxxx  0.2694733831          p4205|p42|p104|p182|p238         5   TRUE
## 642    xxx0x -1.3248172168               p4205|p42|p104|p238         4  FALSE
## 643    xx0x0 -1.2923762701                    p4205|p42|p182         3  FALSE
## 644    xx0xx -0.9533284549               p4205|p42|p182|p238         4  FALSE
## 645    xx00x  1.1950828007                    p4205|p42|p238         3  FALSE
##                unique_id enzyme_name measure_type      cond         means
## 1       DHFR_ic75_palmer        DHFR         ic75    palmer  1.2062354930
## 2       DHFR_ic75_palmer        DHFR         ic75    palmer  0.8239107693
## 3       DHFR_ic75_palmer        DHFR         ic75    palmer  0.2172161842
## 4       DHFR_ic75_palmer        DHFR         ic75    palmer  0.0869399897
## 5       DHFR_ic75_palmer        DHFR         ic75    palmer -3.3818358819
## 6       DHFR_ic75_palmer        DHFR         ic75    palmer -7.1891355892
## 7       DHFR_ic75_palmer        DHFR         ic75    palmer  6.8412959859
## 8       DHFR_ic75_palmer        DHFR         ic75    palmer -4.2235981639
## 9       DHFR_ic75_palmer        DHFR         ic75    palmer -1.0190350137
## 10      DHFR_ic75_palmer        DHFR         ic75    palmer -0.5944141171
## 11      DHFR_ic75_palmer        DHFR         ic75    palmer  0.0104543165
## 12      DHFR_ic75_palmer        DHFR         ic75    palmer  1.8693802891
## 13      DHFR_ic75_palmer        DHFR         ic75    palmer -0.4655815508
## 14      DHFR_ic75_palmer        DHFR         ic75    palmer -0.2289452136
## 15      DHFR_ic75_palmer        DHFR         ic75    palmer  0.0443594841
## 16      DHFR_ic75_palmer        DHFR         ic75    palmer  2.4248366377
## 17      DHFR_ic75_palmer        DHFR         ic75    palmer -0.3734793838
## 18      DHFR_ic75_palmer        DHFR         ic75    palmer  0.2155007877
## 19      DHFR_ic75_palmer        DHFR         ic75    palmer -0.3762876201
## 20      DHFR_ic75_palmer        DHFR         ic75    palmer -1.1774922053
## 21      DHFR_ic75_palmer        DHFR         ic75    palmer -3.0809917088
## 22      DHFR_ic75_palmer        DHFR         ic75    palmer  2.5732055642
## 23      DHFR_ic75_palmer        DHFR         ic75    palmer -2.3319717766
## 24      DHFR_ic75_palmer        DHFR         ic75    palmer -0.0456122478
## 25      DHFR_ic75_palmer        DHFR         ic75    palmer  0.1027002613
## 26      DHFR_ic75_palmer        DHFR         ic75    palmer  0.1307275253
## 27      DHFR_ic75_palmer        DHFR         ic75    palmer  1.9214364729
## 28      DHFR_ic75_palmer        DHFR         ic75    palmer  2.2547035770
## 29      DHFR_ic75_palmer        DHFR         ic75    palmer  1.6478415588
## 30      DHFR_ic75_palmer        DHFR         ic75    palmer  0.6951950425
## 31      DHFR_ic75_palmer        DHFR         ic75    palmer  1.7901616616
## 32      DHFR_ic75_palmer        DHFR         ic75    palmer  0.1627485133
## 33      DHFR_ic75_palmer        DHFR         ic75    palmer -0.6411418079
## 34      DHFR_ic75_palmer        DHFR         ic75    palmer  0.5351546470
## 35      DHFR_ic75_palmer        DHFR         ic75    palmer  1.1245241043
## 36      DHFR_ic75_palmer        DHFR         ic75    palmer -1.3228789457
## 37      DHFR_ic75_palmer        DHFR         ic75    palmer -2.6399845605
## 38      DHFR_ic75_palmer        DHFR         ic75    palmer -0.8278135882
## 39      DHFR_ic75_palmer        DHFR         ic75    palmer  0.9472975263
## 40      DHFR_ic75_palmer        DHFR         ic75    palmer -1.8621430146
## 41      DHFR_ic75_palmer        DHFR         ic75    palmer  1.6952992211
## 42      DHFR_ic75_palmer        DHFR         ic75    palmer -0.9917867991
## 43      DHFR_ic75_palmer        DHFR         ic75    palmer  0.7602580277
## 44      DHFR_ic75_palmer        DHFR         ic75    palmer  2.8704376498
## 45      DHFR_ic75_palmer        DHFR         ic75    palmer -0.8496609691
## 46      DHFR_ic75_palmer        DHFR         ic75    palmer  0.2988833330
## 47      DHFR_ic75_palmer        DHFR         ic75    palmer  0.2794516133
## 48      DHFR_ic75_palmer        DHFR         ic75    palmer -0.6590651019
## 49      DHFR_ic75_palmer        DHFR         ic75    palmer  0.4601334499
## 50      DHFR_ic75_palmer        DHFR         ic75    palmer  0.5131687873
## 51      DHFR_ic75_palmer        DHFR         ic75    palmer -0.8931744546
## 52      DHFR_ic75_palmer        DHFR         ic75    palmer -0.9737236775
## 53      DHFR_ic75_palmer        DHFR         ic75    palmer -0.0430876032
## 54      DHFR_ic75_palmer        DHFR         ic75    palmer  0.3528148943
## 55      DHFR_ic75_palmer        DHFR         ic75    palmer -1.0887019893
## 56      DHFR_ic75_palmer        DHFR         ic75    palmer  0.4966773128
## 57      DHFR_ic75_palmer        DHFR         ic75    palmer  0.0248600677
## 58      DHFR_ic75_palmer        DHFR         ic75    palmer -0.6911103475
## 59      DHFR_ic75_palmer        DHFR         ic75    palmer  0.6800591798
## 60      DHFR_ic75_palmer        DHFR         ic75    palmer -1.8036554355
## 61      DHFR_ic75_palmer        DHFR         ic75    palmer  0.1999543556
## 62      DHFR_ic75_palmer        DHFR         ic75    palmer -0.5632148850
## 63      DHFR_ic75_palmer        DHFR         ic75    palmer -0.1737197244
## 64         DHFR_ki_trajg        DHFR           ki     trajg  0.9697491865
## 65         DHFR_ki_trajg        DHFR           ki     trajg  0.4109127529
## 66         DHFR_ki_trajg        DHFR           ki     trajg  0.0820066602
## 67         DHFR_ki_trajg        DHFR           ki     trajg -0.3698938721
## 68         DHFR_ki_trajg        DHFR           ki     trajg -0.4024022633
## 69         DHFR_ki_trajg        DHFR           ki     trajg -0.3746933214
## 70         DHFR_ki_trajg        DHFR           ki     trajg -0.1078647001
## 71         DHFR_ki_trajg        DHFR           ki     trajg  0.3260605832
## 72         DHFR_ki_trajg        DHFR           ki     trajg  0.0776194738
## 73         DHFR_ki_trajg        DHFR           ki     trajg  0.0773038378
## 74         DHFR_ki_trajg        DHFR           ki     trajg  0.4387885429
## 75         DHFR_ki_trajg        DHFR           ki     trajg  1.6725909180
## 76         DHFR_ki_trajg        DHFR           ki     trajg -0.2379599604
## 77         DHFR_ki_trajg        DHFR           ki     trajg  0.2140346062
## 78         DHFR_ki_trajg        DHFR           ki     trajg -0.5594039435
## 79         DHFR_ki_trajg        DHFR           ki     trajg  0.0156588163
## 80         DHFR_ki_trajg        DHFR           ki     trajg  1.1162865010
## 81         DHFR_ki_trajg        DHFR           ki     trajg  0.4024060198
## 82         DHFR_ki_trajg        DHFR           ki     trajg -0.1485079546
## 83         DHFR_ki_trajg        DHFR           ki     trajg  0.1600164727
## 84         DHFR_ki_trajg        DHFR           ki     trajg -0.0308886904
## 85         DHFR_ki_trajg        DHFR           ki     trajg  0.4189568454
## 86         DHFR_ki_trajg        DHFR           ki     trajg -0.0180350968
## 87         DHFR_ki_trajg        DHFR           ki     trajg  0.2569441197
## 88         DHFR_ki_trajg        DHFR           ki     trajg  1.3968094488
## 89         DHFR_ki_trajg        DHFR           ki     trajg -0.2775070636
## 90         DHFR_ki_trajg        DHFR           ki     trajg -0.7159940330
## 91         DHFR_ki_trajg        DHFR           ki     trajg -0.2978344832
## 92         DHFR_ki_trajg        DHFR           ki     trajg  1.3184002269
## 93         DHFR_ki_trajg        DHFR           ki     trajg  0.5356077160
## 94         DHFR_ki_trajg        DHFR           ki     trajg  1.4946366750
## 95         DHFR_ki_trajr        DHFR           ki     trajr  0.9837809276
## 96         DHFR_ki_trajr        DHFR           ki     trajr  0.2391675950
## 97         DHFR_ki_trajr        DHFR           ki     trajr  0.4455707916
## 98         DHFR_ki_trajr        DHFR           ki     trajr  0.3572343908
## 99         DHFR_ki_trajr        DHFR           ki     trajr -0.4985709562
## 100        DHFR_ki_trajr        DHFR           ki     trajr -0.4227776679
## 101        DHFR_ki_trajr        DHFR           ki     trajr -0.4513550160
## 102        DHFR_ki_trajr        DHFR           ki     trajr  0.1502588862
## 103        DHFR_ki_trajr        DHFR           ki     trajr -0.0102813748
## 104        DHFR_ki_trajr        DHFR           ki     trajr -0.1460729622
## 105        DHFR_ki_trajr        DHFR           ki     trajr -0.0079650572
## 106        DHFR_ki_trajr        DHFR           ki     trajr  1.0204882392
## 107        DHFR_ki_trajr        DHFR           ki     trajr -0.5640112998
## 108        DHFR_ki_trajr        DHFR           ki     trajr  0.2420980885
## 109        DHFR_ki_trajr        DHFR           ki     trajr -0.0307196048
## 110        DHFR_ki_trajr        DHFR           ki     trajr  0.2800009857
## 111        DHFR_ki_trajr        DHFR           ki     trajr  0.9702638982
## 112        DHFR_ki_trajr        DHFR           ki     trajr  0.0922497590
## 113        DHFR_ki_trajr        DHFR           ki     trajr -0.7688204762
## 114        DHFR_ki_trajr        DHFR           ki     trajr -0.6872644817
## 115        DHFR_ki_trajr        DHFR           ki     trajr -0.4545291676
## 116        DHFR_ki_trajr        DHFR           ki     trajr  0.1269116399
## 117        DHFR_ki_trajr        DHFR           ki     trajr  0.4075661730
## 118        DHFR_ki_trajr        DHFR           ki     trajr  0.4697447546
## 119        DHFR_ki_trajr        DHFR           ki     trajr  1.5598421003
## 120        DHFR_ki_trajr        DHFR           ki     trajr  0.0485582393
## 121        DHFR_ki_trajr        DHFR           ki     trajr -0.2779476645
## 122        DHFR_ki_trajr        DHFR           ki     trajr -0.0788112990
## 123        DHFR_ki_trajr        DHFR           ki     trajr  0.9680966144
## 124        DHFR_ki_trajr        DHFR           ki     trajr -0.0381671545
## 125        DHFR_ki_trajr        DHFR           ki     trajr  1.2077492397
## 126     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6014530846
## 127     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.0454450320
## 128     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.0262381099
## 129     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.0298359555
## 130     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.1305570369
## 131     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.0829901928
## 132     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.1933522503
## 133     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6141302903
## 134     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6419418606
## 135     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.5759713003
## 136     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.5753711677
## 137     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.0779951552
## 138     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.4725758154
## 139     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6166938011
## 140     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6761999762
## 141     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.5888533443
## 142     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.7147608105
## 143     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.0329280268
## 144     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.1735958962
## 145     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.6987406300
## 146     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.1183799787
## 147     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.2389949571
## 148     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.0179745831
## 149     MPH_catact_ZnPTM         MPH       catact     ZnPTM  1.3320209103
## 150     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.5190551772
## 151     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.0547379301
## 152     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.0780273638
## 153     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6575819217
## 154     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.1822762261
## 155     MPH_catact_ZnPTM         MPH       catact     ZnPTM  1.1382346025
## 156     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6027861091
## 157       NfsA_ec50_2039        NfsA         ec50      2039 -0.1836051261
## 158       NfsA_ec50_2039        NfsA         ec50      2039  0.0681046216
## 159       NfsA_ec50_2039        NfsA         ec50      2039 -0.0186503117
## 160       NfsA_ec50_2039        NfsA         ec50      2039 -0.0062579777
## 161       NfsA_ec50_2039        NfsA         ec50      2039  0.0916418075
## 162       NfsA_ec50_2039        NfsA         ec50      2039 -0.1062233107
## 163       NfsA_ec50_2039        NfsA         ec50      2039  0.0752331625
## 164       NfsA_ec50_2039        NfsA         ec50      2039 -0.0067424598
## 165       NfsA_ec50_2039        NfsA         ec50      2039 -0.0365279925
## 166       NfsA_ec50_2039        NfsA         ec50      2039  0.0386176943
## 167       NfsA_ec50_2039        NfsA         ec50      2039 -0.0364612571
## 168       NfsA_ec50_2039        NfsA         ec50      2039 -0.1043226875
## 169       NfsA_ec50_2039        NfsA         ec50      2039  0.2455043396
## 170       NfsA_ec50_2039        NfsA         ec50      2039 -0.0039551835
## 171       NfsA_ec50_2039        NfsA         ec50      2039  0.3517777861
## 172       NfsA_ec50_2039        NfsA         ec50      2039  0.0709342958
## 173       NfsA_ec50_2039        NfsA         ec50      2039 -0.0105120513
## 174       NfsA_ec50_2039        NfsA         ec50      2039 -0.0298045492
## 175       NfsA_ec50_2039        NfsA         ec50      2039 -0.0255586573
## 176       NfsA_ec50_2039        NfsA         ec50      2039  0.0695594275
## 177       NfsA_ec50_2039        NfsA         ec50      2039  0.0428042028
## 178       NfsA_ec50_2039        NfsA         ec50      2039  0.0337737283
## 179       NfsA_ec50_2039        NfsA         ec50      2039 -0.0359432925
## 180       NfsA_ec50_2039        NfsA         ec50      2039 -0.0903033454
## 181       NfsA_ec50_2039        NfsA         ec50      2039 -0.0556827046
## 182       NfsA_ec50_2039        NfsA         ec50      2039 -0.0281368788
## 183       NfsA_ec50_2039        NfsA         ec50      2039 -0.0177819590
## 184       NfsA_ec50_2039        NfsA         ec50      2039 -0.1324799126
## 185       NfsA_ec50_2039        NfsA         ec50      2039 -0.0358644364
## 186       NfsA_ec50_2039        NfsA         ec50      2039 -0.2410580287
## 187       NfsA_ec50_2039        NfsA         ec50      2039  0.1397653277
## 188       NfsA_ec50_2039        NfsA         ec50      2039  0.0963359828
## 189       NfsA_ec50_2039        NfsA         ec50      2039  0.1058026609
## 190       NfsA_ec50_2039        NfsA         ec50      2039  0.0075018912
## 191       NfsA_ec50_2039        NfsA         ec50      2039 -0.0220382404
## 192       NfsA_ec50_2039        NfsA         ec50      2039  0.0328627091
## 193       NfsA_ec50_2039        NfsA         ec50      2039  0.0912835621
## 194       NfsA_ec50_2039        NfsA         ec50      2039 -0.0629425668
## 195       NfsA_ec50_2039        NfsA         ec50      2039  0.0346434105
## 196       NfsA_ec50_2039        NfsA         ec50      2039  0.0975715483
## 197       NfsA_ec50_2039        NfsA         ec50      2039 -0.0173590203
## 198       NfsA_ec50_2039        NfsA         ec50      2039  0.0653162028
## 199       NfsA_ec50_2039        NfsA         ec50      2039 -0.1337930941
## 200       NfsA_ec50_2039        NfsA         ec50      2039  0.2123040146
## 201       NfsA_ec50_2039        NfsA         ec50      2039  0.0339294274
## 202       NfsA_ec50_2039        NfsA         ec50      2039  0.2326842483
## 203       NfsA_ec50_2039        NfsA         ec50      2039  0.0906688737
## 204       NfsA_ec50_2039        NfsA         ec50      2039 -0.0193446645
## 205       NfsA_ec50_2039        NfsA         ec50      2039 -0.0274577404
## 206       NfsA_ec50_2039        NfsA         ec50      2039 -0.0044199260
## 207       NfsA_ec50_2039        NfsA         ec50      2039  0.0062850048
## 208       NfsA_ec50_2039        NfsA         ec50      2039 -0.0280033491
## 209       NfsA_ec50_2039        NfsA         ec50      2039 -0.0146378985
## 210       NfsA_ec50_2039        NfsA         ec50      2039 -0.0229229906
## 211       NfsA_ec50_2039        NfsA         ec50      2039 -0.0166336540
## 212       NfsA_ec50_2039        NfsA         ec50      2039  0.0163758077
## 213       NfsA_ec50_2039        NfsA         ec50      2039 -0.0629292093
## 214       NfsA_ec50_2039        NfsA         ec50      2039 -0.0978057282
## 215       NfsA_ec50_2039        NfsA         ec50      2039 -0.1077205690
## 216       NfsA_ec50_2039        NfsA         ec50      2039  0.0521695212
## 217       NfsA_ec50_2039        NfsA         ec50      2039  0.4787066672
## 218       NfsA_ec50_2039        NfsA         ec50      2039  0.2889894811
## 219       NfsA_ec50_2039        NfsA         ec50      2039  0.1275384125
## 220       NfsA_ec50_2039        NfsA         ec50      2039  0.3094435780
## 221       NfsA_ec50_2039        NfsA         ec50      2039  0.3579534467
## 222       NfsA_ec50_2039        NfsA         ec50      2039 -0.1455269649
## 223       NfsA_ec50_2039        NfsA         ec50      2039  0.0204132770
## 224       NfsA_ec50_2039        NfsA         ec50      2039 -0.0004683640
## 225       NfsA_ec50_2039        NfsA         ec50      2039  0.0200263949
## 226       NfsA_ec50_2039        NfsA         ec50      2039  0.2315052064
## 227       NfsA_ec50_2039        NfsA         ec50      2039  0.3065119830
## 228       NfsA_ec50_2039        NfsA         ec50      2039  0.0355119615
## 229       NfsA_ec50_2039        NfsA         ec50      2039  0.1239119618
## 230       NfsA_ec50_2039        NfsA         ec50      2039  0.1770238631
## 231       NfsA_ec50_2039        NfsA         ec50      2039 -0.0211872665
## 232       NfsA_ec50_2039        NfsA         ec50      2039  0.2825320265
## 233       NfsA_ec50_2039        NfsA         ec50      2039 -0.3709280451
## 234       NfsA_ec50_2039        NfsA         ec50      2039 -0.0382235176
## 235       NfsA_ec50_2039        NfsA         ec50      2039 -0.0089850783
## 236       NfsA_ec50_2039        NfsA         ec50      2039 -0.4119726269
## 237       NfsA_ec50_2039        NfsA         ec50      2039 -0.1245892565
## 238       NfsA_ec50_2039        NfsA         ec50      2039  0.0745672884
## 239       NfsA_ec50_2039        NfsA         ec50      2039 -0.0478116786
## 240       NfsA_ec50_2039        NfsA         ec50      2039  0.0303642996
## 241       NfsA_ec50_2039        NfsA         ec50      2039 -0.2624441094
## 242       NfsA_ec50_2039        NfsA         ec50      2039 -0.0812688215
## 243       NfsA_ec50_2039        NfsA         ec50      2039  0.0529152655
## 244       NfsA_ec50_2039        NfsA         ec50      2039  0.2146652139
## 245       NfsA_ec50_2039        NfsA         ec50      2039  0.0783215107
## 246       NfsA_ec50_2039        NfsA         ec50      2039  0.0891218831
## 247       NfsA_ec50_2039        NfsA         ec50      2039 -0.0297717435
## 248       NfsA_ec50_2039        NfsA         ec50      2039  0.0468898238
## 249       NfsA_ec50_2039        NfsA         ec50      2039 -0.0227298126
## 250       NfsA_ec50_2039        NfsA         ec50      2039  0.5286519492
## 251       NfsA_ec50_2039        NfsA         ec50      2039 -0.0403094169
## 252       NfsA_ec50_2039        NfsA         ec50      2039 -0.1051249211
## 253       NfsA_ec50_2039        NfsA         ec50      2039  0.0073342133
## 254       NfsA_ec50_2039        NfsA         ec50      2039 -0.0252371270
## 255       NfsA_ec50_2039        NfsA         ec50      2039 -0.0236105839
## 256       NfsA_ec50_2039        NfsA         ec50      2039  0.1727504818
## 257       NfsA_ec50_2039        NfsA         ec50      2039 -0.0086689450
## 258       NfsA_ec50_2039        NfsA         ec50      2039  0.1369784273
## 259       NfsA_ec50_2039        NfsA         ec50      2039  0.0017264238
## 260       NfsA_ec50_2039        NfsA         ec50      2039  0.0432167804
## 261       NfsA_ec50_2039        NfsA         ec50      2039  0.0005318277
## 262       NfsA_ec50_2039        NfsA         ec50      2039  0.0516320608
## 263       NfsA_ec50_2039        NfsA         ec50      2039  0.0512407834
## 264       NfsA_ec50_2039        NfsA         ec50      2039 -0.0392870444
## 265       NfsA_ec50_2039        NfsA         ec50      2039  0.0058148649
## 266       NfsA_ec50_2039        NfsA         ec50      2039  0.0040635316
## 267       NfsA_ec50_2039        NfsA         ec50      2039 -0.0364234226
## 268       NfsA_ec50_2039        NfsA         ec50      2039 -0.0651786412
## 269       NfsA_ec50_2039        NfsA         ec50      2039  0.0377675481
## 270       NfsA_ec50_2039        NfsA         ec50      2039  0.0357611152
## 271       NfsA_ec50_2039        NfsA         ec50      2039  0.0795724700
## 272       NfsA_ec50_2039        NfsA         ec50      2039  0.0143172459
## 273       NfsA_ec50_2039        NfsA         ec50      2039 -0.0049343146
## 274       NfsA_ec50_2039        NfsA         ec50      2039  0.0165982946
## 275       NfsA_ec50_2039        NfsA         ec50      2039  0.0251150682
## 276       NfsA_ec50_2039        NfsA         ec50      2039  0.0117068309
## 277       NfsA_ec50_2039        NfsA         ec50      2039  0.0584999147
## 278       NfsA_ec50_2039        NfsA         ec50      2039  0.1708262589
## 279       NfsA_ec50_2039        NfsA         ec50      2039 -0.0262790812
## 280       NfsA_ec50_2039        NfsA         ec50      2039 -0.0353591048
## 281       NfsA_ec50_2039        NfsA         ec50      2039  0.5323078372
## 282       NfsA_ec50_2039        NfsA         ec50      2039 -0.0762717891
## 283       NfsA_ec50_2039        NfsA         ec50      2039 -0.1138374545
## 284       NfsA_ec50_3637        NfsA         ec50      3637 -0.0569706652
## 285       NfsA_ec50_3637        NfsA         ec50      3637  0.0207202924
## 286       NfsA_ec50_3637        NfsA         ec50      3637  0.0617297495
## 287       NfsA_ec50_3637        NfsA         ec50      3637 -0.1321747554
## 288       NfsA_ec50_3637        NfsA         ec50      3637  0.2251203280
## 289       NfsA_ec50_3637        NfsA         ec50      3637  0.9181359551
## 290       NfsA_ec50_3637        NfsA         ec50      3637 -0.2032811849
## 291       NfsA_ec50_3637        NfsA         ec50      3637 -0.0733541727
## 292       NfsA_ec50_3637        NfsA         ec50      3637 -0.3954314003
## 293       NfsA_ec50_3637        NfsA         ec50      3637  0.1603000840
## 294       NfsA_ec50_3637        NfsA         ec50      3637  0.0692931523
## 295       NfsA_ec50_3637        NfsA         ec50      3637  0.0172715963
## 296       NfsA_ec50_3637        NfsA         ec50      3637 -0.2790421770
## 297       NfsA_ec50_3637        NfsA         ec50      3637  0.0926146264
## 298       NfsA_ec50_3637        NfsA         ec50      3637  0.2187172032
## 299       NfsA_ec50_3637        NfsA         ec50      3637 -0.2894908905
## 300       NfsA_ec50_3637        NfsA         ec50      3637 -0.1314996851
## 301       NfsA_ec50_3637        NfsA         ec50      3637 -0.0734456760
## 302       NfsA_ec50_3637        NfsA         ec50      3637 -0.0248115637
## 303       NfsA_ec50_3637        NfsA         ec50      3637 -0.2871770486
## 304       NfsA_ec50_3637        NfsA         ec50      3637 -0.1946197462
## 305       NfsA_ec50_3637        NfsA         ec50      3637  0.0122059190
## 306       NfsA_ec50_3637        NfsA         ec50      3637  0.0057623657
## 307       NfsA_ec50_3637        NfsA         ec50      3637  0.0236221014
## 308       NfsA_ec50_3637        NfsA         ec50      3637 -0.0741606229
## 309       NfsA_ec50_3637        NfsA         ec50      3637  0.0225808245
## 310       NfsA_ec50_3637        NfsA         ec50      3637  0.1432529308
## 311       NfsA_ec50_3637        NfsA         ec50      3637  0.1044974531
## 312       NfsA_ec50_3637        NfsA         ec50      3637 -0.1794361674
## 313       NfsA_ec50_3637        NfsA         ec50      3637 -0.1712352281
## 314       NfsA_ec50_3637        NfsA         ec50      3637  0.1681112032
## 315       NfsA_ec50_3637        NfsA         ec50      3637  0.1876979101
## 316       NfsA_ec50_3637        NfsA         ec50      3637  0.1242066126
## 317       NfsA_ec50_3637        NfsA         ec50      3637  0.0060707290
## 318       NfsA_ec50_3637        NfsA         ec50      3637  0.0273060835
## 319       NfsA_ec50_3637        NfsA         ec50      3637 -0.0580679126
## 320       NfsA_ec50_3637        NfsA         ec50      3637 -0.1621399356
## 321       NfsA_ec50_3637        NfsA         ec50      3637 -0.0461866784
## 322       NfsA_ec50_3637        NfsA         ec50      3637  0.0826201157
## 323       NfsA_ec50_3637        NfsA         ec50      3637  0.0611866980
## 324       NfsA_ec50_3637        NfsA         ec50      3637 -0.0234087043
## 325       NfsA_ec50_3637        NfsA         ec50      3637  0.0748541626
## 326       NfsA_ec50_3637        NfsA         ec50      3637  0.0553774954
## 327       NfsA_ec50_3637        NfsA         ec50      3637  0.0922134343
## 328       NfsA_ec50_3637        NfsA         ec50      3637 -0.0564313255
## 329       NfsA_ec50_3637        NfsA         ec50      3637  0.0927015930
## 330       NfsA_ec50_3637        NfsA         ec50      3637 -0.1914053813
## 331       NfsA_ec50_3637        NfsA         ec50      3637  0.0034482452
## 332       NfsA_ec50_3637        NfsA         ec50      3637  0.0743519850
## 333       NfsA_ec50_3637        NfsA         ec50      3637 -0.0222180181
## 334       NfsA_ec50_3637        NfsA         ec50      3637  0.1118174567
## 335       NfsA_ec50_3637        NfsA         ec50      3637  0.1675711646
## 336       NfsA_ec50_3637        NfsA         ec50      3637 -0.0544554698
## 337       NfsA_ec50_3637        NfsA         ec50      3637 -0.0782406699
## 338       NfsA_ec50_3637        NfsA         ec50      3637 -0.1210110456
## 339       NfsA_ec50_3637        NfsA         ec50      3637  0.0633115530
## 340       NfsA_ec50_3637        NfsA         ec50      3637 -0.0562297539
## 341       NfsA_ec50_3637        NfsA         ec50      3637  0.3126121933
## 342       NfsA_ec50_3637        NfsA         ec50      3637 -0.0750305493
## 343       NfsA_ec50_3637        NfsA         ec50      3637 -0.0653991572
## 344       NfsA_ec50_3637        NfsA         ec50      3637  0.6005381669
## 345       NfsA_ec50_3637        NfsA         ec50      3637  0.0523536890
## 346       NfsA_ec50_3637        NfsA         ec50      3637  0.1660586859
## 347       NfsA_ec50_3637        NfsA         ec50      3637  0.2481057780
## 348       NfsA_ec50_3637        NfsA         ec50      3637  0.2334684124
## 349       NfsA_ec50_3637        NfsA         ec50      3637 -0.0902993257
## 350       NfsA_ec50_3637        NfsA         ec50      3637  0.1100160218
## 351       NfsA_ec50_3637        NfsA         ec50      3637 -0.4441508278
## 352       NfsA_ec50_3637        NfsA         ec50      3637  0.1480407335
## 353       NfsA_ec50_3637        NfsA         ec50      3637  1.9130554790
## 354       NfsA_ec50_3637        NfsA         ec50      3637  0.0349365724
## 355       NfsA_ec50_3637        NfsA         ec50      3637 -0.1825827093
## 356       NfsA_ec50_3637        NfsA         ec50      3637 -0.1683354659
## 357       NfsA_ec50_3637        NfsA         ec50      3637  0.2066348605
## 358       NfsA_ec50_3637        NfsA         ec50      3637  0.1466547909
## 359       NfsA_ec50_3637        NfsA         ec50      3637 -0.0751033646
## 360       NfsA_ec50_3637        NfsA         ec50      3637  0.2172275239
## 361       NfsA_ec50_3637        NfsA         ec50      3637  0.2265367060
## 362       NfsA_ec50_3637        NfsA         ec50      3637 -0.2405484081
## 363       NfsA_ec50_3637        NfsA         ec50      3637 -0.0482498806
## 364       NfsA_ec50_3637        NfsA         ec50      3637  0.1296145456
## 365       NfsA_ec50_3637        NfsA         ec50      3637  0.1452661161
## 366       NfsA_ec50_3637        NfsA         ec50      3637  0.0166145089
## 367       NfsA_ec50_3637        NfsA         ec50      3637 -0.1953665691
## 368       NfsA_ec50_3637        NfsA         ec50      3637  0.5683588741
## 369       NfsA_ec50_3637        NfsA         ec50      3637  0.2764296357
## 370       NfsA_ec50_3637        NfsA         ec50      3637  0.1256842504
## 371       NfsA_ec50_3637        NfsA         ec50      3637  0.4798621280
## 372       NfsA_ec50_3637        NfsA         ec50      3637  0.1207426029
## 373       NfsA_ec50_3637        NfsA         ec50      3637 -0.1216801227
## 374       NfsA_ec50_3637        NfsA         ec50      3637 -0.0055669317
## 375       NfsA_ec50_3637        NfsA         ec50      3637  0.3247082162
## 376       NfsA_ec50_3637        NfsA         ec50      3637 -0.1909947989
## 377       NfsA_ec50_3637        NfsA         ec50      3637  0.2095135629
## 378       NfsA_ec50_3637        NfsA         ec50      3637 -0.4965798123
## 379       NfsA_ec50_3637        NfsA         ec50      3637 -0.1818802618
## 380       NfsA_ec50_3637        NfsA         ec50      3637 -0.0123674545
## 381       NfsA_ec50_3637        NfsA         ec50      3637 -0.0199667765
## 382       NfsA_ec50_3637        NfsA         ec50      3637  0.1093012756
## 383       NfsA_ec50_3637        NfsA         ec50      3637 -0.1985136418
## 384       NfsA_ec50_3637        NfsA         ec50      3637 -0.4374371314
## 385       NfsA_ec50_3637        NfsA         ec50      3637  0.0334701705
## 386       NfsA_ec50_3637        NfsA         ec50      3637  0.1032024493
## 387       NfsA_ec50_3637        NfsA         ec50      3637 -0.1092382943
## 388       NfsA_ec50_3637        NfsA         ec50      3637 -0.0813533852
## 389       NfsA_ec50_3637        NfsA         ec50      3637 -0.1803026806
## 390       NfsA_ec50_3637        NfsA         ec50      3637 -0.0089813811
## 391       NfsA_ec50_3637        NfsA         ec50      3637  0.3256607652
## 392       NfsA_ec50_3637        NfsA         ec50      3637 -0.0887530639
## 393       NfsA_ec50_3637        NfsA         ec50      3637 -0.0427680980
## 394       NfsA_ec50_3637        NfsA         ec50      3637 -0.1243121143
## 395       NfsA_ec50_3637        NfsA         ec50      3637  0.2248910047
## 396       NfsA_ec50_3637        NfsA         ec50      3637  0.0124182728
## 397       NfsA_ec50_3637        NfsA         ec50      3637 -0.1179390815
## 398       NfsA_ec50_3637        NfsA         ec50      3637  0.2463504336
## 399       NfsA_ec50_3637        NfsA         ec50      3637 -0.0788818339
## 400       NfsA_ec50_3637        NfsA         ec50      3637 -0.0385841910
## 401       NfsA_ec50_3637        NfsA         ec50      3637  0.0355885181
## 402       NfsA_ec50_3637        NfsA         ec50      3637 -0.2867550554
## 403       NfsA_ec50_3637        NfsA         ec50      3637 -0.0555546182
## 404       NfsA_ec50_3637        NfsA         ec50      3637 -0.0906614568
## 405       NfsA_ec50_3637        NfsA         ec50      3637  0.0375301472
## 406       NfsA_ec50_3637        NfsA         ec50      3637  0.0669668060
## 407       NfsA_ec50_3637        NfsA         ec50      3637  0.1206408259
## 408       NfsA_ec50_3637        NfsA         ec50      3637  0.2984792456
## 409       NfsA_ec50_3637        NfsA         ec50      3637 -0.3608554723
## 410       NfsA_ec50_3637        NfsA         ec50      3637 -0.0562624733
## 411 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.3320456373
## 412 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.0018436095
## 413 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.3308587296
## 414 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.0257601887
## 415 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.0309832222
## 416 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.1279913659
## 417 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.0362998491
## 418 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.0051600705
## 419 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.2345885840
## 420 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.2724234489
## 421 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.0021184273
## 422 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.9278873633
## 423 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.4520073760
## 424 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.4140018406
## 425 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.5298022887
## 426 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.5072447682
## 427 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2322662635
## 428 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2011161233
## 429 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.3675270797
## 430 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0776672023
## 431 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2575459450
## 432 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1957446004
## 433 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1469379670
## 434 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1729186185
## 435 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1034867917
## 436 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0245774437
## 437 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0962601272
## 438 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.3783664636
## 439 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0374030371
## 440 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.3571733510
## 441 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1761771660
## 442 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2310929181
## 443 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1550315534
## 444 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0836030575
## 445 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2079829987
## 446 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0636474609
## 447 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1537873915
## 448 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.3862382251
## 449 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1370188947
## 450 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1334705379
## 451 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0620513175
## 452 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0826698657
## 453 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0804127445
## 454 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1021430941
## 455 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0291861163
## 456 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1708379190
## 457 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1726222318
## 458 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0526166129
## 459 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0839710533
## 460 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0835174321
## 461 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2371716121
## 462 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0177659322
## 463 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0023086958
## 464 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1701052593
## 465 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2339087945
## 466 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1575969765
## 467 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1286436265
## 468 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2046346501
## 469 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1116113314
## 470 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.3103155767
## 471 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1005210644
## 472 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1105589638
## 473 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2858996573
## 474 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2687554330
## 475 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0179728892
## 476 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1203778663
## 477 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0130191319
## 478 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2929293612
## 479 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1523968960
## 480 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2308520929
## 481 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1963371276
## 482 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1482655882
## 483 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1611956215
## 484 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1346938665
## 485 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2240176489
## 486 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0151834977
## 487 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0503255758
## 488 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1977983004
## 489 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0610598579
## 490 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0409902741
## 491 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0960047615
## 492 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0319766797
## 493 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.2597174797
## 494 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1646899644
## 495 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0126269844
## 496 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0418167864
## 497 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1029315531
## 498 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0897087574
## 499 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0399018082
## 500 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0179960429
## 501 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0975201602
## 502 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0398744580
## 503 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0192487103
## 504 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0011875442
## 505 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0520545989
## 506 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1274031534
## 507 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0016661053
## 508 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0788291217
## 509 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1658703587
## 510 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0128113183
## 511 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0273208218
## 512 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0032190631
## 513 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.7306148862
## 514 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0337077327
## 515 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0415368472
## 516 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1253463593
## 517 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0134890705
## 518 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0119185296
## 519 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0273295870
## 520 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.3584109834
## 521 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0458425116
## 522 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1030318338
## 523 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0849993482
## 524 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.2143528103
## 525 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.4726135136
## 526 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.2156369908
## 527 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1649320251
## 528 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1671852596
## 529 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0842277227
## 530 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1740119280
## 531 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0864575198
## 532 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0255847522
## 533 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0514435847
## 534 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0684301233
## 535 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.2718614986
## 536 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0723157477
## 537 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0957845105
## 538 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1378797455
## 539 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1277320188
## 540 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.3382977306
## 541 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0046617010
## 542 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0642127088
## 543 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1439535601
## 544 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0021469899
## 545 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.6629417155
## 546 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0106092530
## 547 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0314345394
## 548 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1211614184
## 549 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0413610788
## 550 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0566767551
## 551 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0922228366
## 552       PTE_catact_2NH         PTE       catact       2NH  0.7285390388
## 553       PTE_catact_2NH         PTE       catact       2NH  0.6373364226
## 554       PTE_catact_2NH         PTE       catact       2NH -0.2450705571
## 555       PTE_catact_2NH         PTE       catact       2NH -0.4956750948
## 556       PTE_catact_2NH         PTE       catact       2NH -0.6668673267
## 557       PTE_catact_2NH         PTE       catact       2NH  0.2725240242
## 558       PTE_catact_2NH         PTE       catact       2NH -0.5812863605
## 559       PTE_catact_2NH         PTE       catact       2NH -0.3335239493
## 560       PTE_catact_2NH         PTE       catact       2NH -1.6213040114
## 561       PTE_catact_2NH         PTE       catact       2NH -0.2268754483
## 562       PTE_catact_2NH         PTE       catact       2NH -0.0235867814
## 563       PTE_catact_2NH         PTE       catact       2NH -0.2614621340
## 564       PTE_catact_2NH         PTE       catact       2NH  0.6199565695
## 565       PTE_catact_2NH         PTE       catact       2NH  0.3578151577
## 566       PTE_catact_2NH         PTE       catact       2NH -0.8021822297
## 567       PTE_catact_2NH         PTE       catact       2NH  0.0947106215
## 568       PTE_catact_2NH         PTE       catact       2NH -0.0564936082
## 569       PTE_catact_2NH         PTE       catact       2NH  0.0769863183
## 570       PTE_catact_2NH         PTE       catact       2NH  0.0904603121
## 571       PTE_catact_2NH         PTE       catact       2NH  0.2717675785
## 572       PTE_catact_2NH         PTE       catact       2NH  0.8347845561
## 573       PTE_catact_2NH         PTE       catact       2NH  0.3473048566
## 574       PTE_catact_2NH         PTE       catact       2NH -0.1365751694
## 575       PTE_catact_2NH         PTE       catact       2NH -0.5099230009
## 576       PTE_catact_2NH         PTE       catact       2NH  0.2087296979
## 577       PTE_catact_2NH         PTE       catact       2NH -0.4068882602
## 578       PTE_catact_2NH         PTE       catact       2NH -0.2946447369
## 579       PTE_catact_2NH         PTE       catact       2NH -0.2780698745
## 580       PTE_catact_2NH         PTE       catact       2NH -0.1593031117
## 581       PTE_catact_2NH         PTE       catact       2NH -0.5955769994
## 582       PTE_catact_2NH         PTE       catact       2NH -0.0596301158
## 583       PTE_catact_2NH         PTE       catact       2NH -0.1570006989
## 584       PTE_catact_2NH         PTE       catact       2NH  1.4715059467
## 585       PTE_catact_2NH         PTE       catact       2NH  0.0137585293
## 586       PTE_catact_2NH         PTE       catact       2NH -0.1103822900
## 587       PTE_catact_2NH         PTE       catact       2NH -0.3977623654
## 588       PTE_catact_2NH         PTE       catact       2NH -0.2347492538
## 589       PTE_catact_2NH         PTE       catact       2NH -0.2301507057
## 590       PTE_catact_2NH         PTE       catact       2NH -0.3752671809
## 591       PTE_catact_2NH         PTE       catact       2NH -1.1402236356
## 592       PTE_catact_2NH         PTE       catact       2NH -0.2300782640
## 593       PTE_catact_2NH         PTE       catact       2NH  0.3597276308
## 594       PTE_catact_2NH         PTE       catact       2NH  0.1752027516
## 595       PTE_catact_2NH         PTE       catact       2NH  0.0086221024
## 596       PTE_catact_2NH         PTE       catact       2NH  0.0744053780
## 597       PTE_catact_2NH         PTE       catact       2NH -0.3127144804
## 598       PTE_catact_2NH         PTE       catact       2NH -0.0655980266
## 599       PTE_catact_2NH         PTE       catact       2NH  0.1022297216
## 600       PTE_catact_2NH         PTE       catact       2NH  0.1688986986
## 601       PTE_catact_2NH         PTE       catact       2NH  0.0224243247
## 602       PTE_catact_2NH         PTE       catact       2NH  0.0256556361
## 603       PTE_catact_2NH         PTE       catact       2NH -0.0935406092
## 604       PTE_catact_2NH         PTE       catact       2NH -0.2015806584
## 605       PTE_catact_2NH         PTE       catact       2NH  0.3272962613
## 606       PTE_catact_2NH         PTE       catact       2NH  0.4764903090
## 607       PTE_catact_2NH         PTE       catact       2NH  0.4376029757
## 608       PTE_catact_2NH         PTE       catact       2NH  0.2179017588
## 609       PTE_catact_2NH         PTE       catact       2NH -0.1814104041
## 610       PTE_catact_2NH         PTE       catact       2NH -0.0949573899
## 611       PTE_catact_2NH         PTE       catact       2NH  0.0065038763
## 612       PTE_catact_2NH         PTE       catact       2NH  1.0105759149
## 613       PTE_catact_2NH         PTE       catact       2NH -0.1228109891
## 614       PTE_catact_2NH         PTE       catact       2NH -0.0440976935
## 615    TEM_MIC_weinreich         TEM          MIC weinreich  0.9959252876
## 616    TEM_MIC_weinreich         TEM          MIC weinreich -0.6380093140
## 617    TEM_MIC_weinreich         TEM          MIC weinreich -0.5617283740
## 618    TEM_MIC_weinreich         TEM          MIC weinreich  0.8173978048
## 619    TEM_MIC_weinreich         TEM          MIC weinreich  0.4404367458
## 620    TEM_MIC_weinreich         TEM          MIC weinreich  0.6828096293
## 621    TEM_MIC_weinreich         TEM          MIC weinreich  2.9983253265
## 622    TEM_MIC_weinreich         TEM          MIC weinreich  0.7668805522
## 623    TEM_MIC_weinreich         TEM          MIC weinreich  0.0416191642
## 624    TEM_MIC_weinreich         TEM          MIC weinreich  0.1349017256
## 625    TEM_MIC_weinreich         TEM          MIC weinreich  2.0614142448
## 626    TEM_MIC_weinreich         TEM          MIC weinreich -1.1026904531
## 627    TEM_MIC_weinreich         TEM          MIC weinreich -0.2531919803
## 628    TEM_MIC_weinreich         TEM          MIC weinreich -0.9029548338
## 629    TEM_MIC_weinreich         TEM          MIC weinreich  0.2946085787
## 630    TEM_MIC_weinreich         TEM          MIC weinreich  0.1589193176
## 631    TEM_MIC_weinreich         TEM          MIC weinreich  0.0340169486
## 632    TEM_MIC_weinreich         TEM          MIC weinreich  0.5607717676
## 633    TEM_MIC_weinreich         TEM          MIC weinreich  0.0323045028
## 634    TEM_MIC_weinreich         TEM          MIC weinreich -0.7790332707
## 635    TEM_MIC_weinreich         TEM          MIC weinreich -0.0333338299
## 636    TEM_MIC_weinreich         TEM          MIC weinreich  0.4991308025
## 637    TEM_MIC_weinreich         TEM          MIC weinreich  0.4495140405
## 638    TEM_MIC_weinreich         TEM          MIC weinreich -0.2029847382
## 639    TEM_MIC_weinreich         TEM          MIC weinreich  0.1679882204
## 640    TEM_MIC_weinreich         TEM          MIC weinreich  1.5870060093
## 641    TEM_MIC_weinreich         TEM          MIC weinreich  0.2694733831
## 642    TEM_MIC_weinreich         TEM          MIC weinreich -1.1900805252
## 643    TEM_MIC_weinreich         TEM          MIC weinreich -0.9755374929
## 644    TEM_MIC_weinreich         TEM          MIC weinreich -0.8185917634
## 645    TEM_MIC_weinreich         TEM          MIC weinreich  0.1233783106
##     traj_effects access access_no_idio access_mean access_w_mean access_w_idio
## 1    0.643452676     NA             NA          NA            NA            NA
## 2    1.383815366      2              2           2             0             0
## 3    1.910624405      3              1           1            -2             2
## 4    2.324282455      3              4           4             1            -1
## 5    2.103803721      0              0           0             0             0
## 6    2.158362492      2              6           2             0            -4
## 7    2.294466226      3              0           1            -2             3
## 8    2.222716471      4              4           1            -3             0
## 9    2.313867220      5              0           0            -5             5
## 10   2.227886705      4              4           4             0             0
## 11   2.071882007      3              1           1            -2             2
## 12   2.184691431      3              1           2            -1             2
## 13   2.278753601      4              2           2            -2             2
## 14  -3.031517051      0              3           1             1            -3
## 15   1.856124444      3              3           3             0             0
## 16   1.710963119      1              1           4             3             0
## 17   1.983175072      3              1           0            -3             2
## 18   1.146128036      2              2           2             0             0
## 19   2.342422681      3              3           2            -1             0
## 20   2.322219295      3              0           0            -3             3
## 21   2.324282455      4              1           0            -4             3
## 22   2.326335861      3              4           4             1            -1
## 23   2.086359831      3              3           0            -3             0
## 24   2.217483944      4              1           1            -3             3
## 25   2.049218023      3              2           2            -1             1
## 26   1.933993164      2              2           2             0             0
## 27   2.320146286      3              3           3             0             0
## 28   2.311753861      3              1           4             1             2
## 29   2.283301229      3              0           3             0             3
## 30   1.713490543      2              2           2             0             0
## 31   2.082785370      3              3           3             0             0
## 32   1.557507202      2              2           2             0             0
## 33   0.728353782     NA             NA          NA            NA            NA
## 34  -3.031517051      0              2           2             2            -2
## 35   0.717670503      1              1           1             0             0
## 36   2.324282455      4              4           2            -2             0
## 37  -0.798602876      1              1           0            -1             0
## 38  -0.422508200      0              4           4             4            -4
## 39   1.187520721      3              1           1            -2             2
## 40   1.973589623      4              4           4             0             0
## 41   1.363611980      3              0           1            -2             3
## 42   1.187520721      1              2           1             0            -1
## 43  -0.804100348      0              1           2             2            -1
## 44  -3.031517051      0              0           0             0             0
## 45  -0.277366077      0              0           0             0             0
## 46   0.706717782      1              2           2             1            -1
## 47  -0.543633967      0              2           2             2            -2
## 48   0.822821645      1              2           2             1            -1
## 49   0.307496038     NA             NA          NA            NA            NA
## 50   2.193124598      2              2           2             0             0
## 51   2.079181246      2              3           1            -1            -1
## 52  -0.228412519      0              0           0             0             0
## 53   2.049218023      2              1           1            -1             1
## 54   1.025305865      2              2           2             0             0
## 55   1.557507202      2              3           0            -2            -1
## 56   1.049218023      1              2           2             1            -1
## 57   1.855519156     NA             NA          NA            NA            NA
## 58   1.824125834      1              2           1             0            -1
## 59  -0.157390760      0              2           3             3            -2
## 60   1.692846919      1              2           1             0            -1
## 61   0.267171728     NA             NA          NA            NA            NA
## 62   1.964730921      2              2           1            -1             0
## 63   1.472756449     NA             NA          NA            NA            NA
## 64   0.352182518     NA             NA          NA            NA            NA
## 65   1.025305865      2              2           2             0             0
## 66   3.082785370      3              3           3             0             0
## 67   4.389166084      4              4           4             0             0
## 68   5.965671971      5              5           5             0             0
## 69   4.281033367      4              4           4             0             0
## 70   2.606381365      3              3           3             0             0
## 71   4.658964843      4              4           4             0             0
## 72   2.799340549      3              3           3             0             0
## 73   1.700703717      2              2           2             0             0
## 74   2.870988814      3              3           3             0             0
## 75   4.198657087      4              0           4             0             4
## 76   2.774516966      3              3           3             0             0
## 77   1.484299839      2              2           2             0             0
## 78   3.049218023      3              3           3             0             0
## 79   1.804139432      2              2           2             0             0
## 80   0.342422681     NA             NA          NA            NA            NA
## 81   1.828015064      2              2           2             0             0
## 82   3.017033339      3              3           3             0             0
## 83   4.582063363      4              4           4             0             0
## 84   3.354108439      3              3           3             0             0
## 85   1.324282455      2              2           2             0             0
## 86   3.675778342      3              3           3             0             0
## 87   1.283301229      2              2           2             0             0
## 88   1.130333768     NA             NA          NA            NA            NA
## 89   1.828015064      2              2           2             0             0
## 90   3.096910013      3              3           3             0             0
## 91   2.359835482      2              2           2             0             0
## 92   0.346352974     NA             NA          NA            NA            NA
## 93   2.738780558      2              2           2             0             0
## 94   0.620136055     NA             NA          NA            NA            NA
## 95   0.352182518     NA             NA          NA            NA            NA
## 96   1.025305865      2              2           2             0             0
## 97   3.082785370      3              3           3             0             0
## 98   3.962369336      4              4           4             0             0
## 99   5.230448921      5              5           5             0             0
## 100  4.281033367      4              4           4             0             0
## 101  2.037426498      3              3           3             0             0
## 102  4.117271296      4              4           4             0             0
## 103  2.799340549      3              3           3             0             0
## 104  1.700703717      2              2           2             0             0
## 105  2.981365509      3              3           3             0             0
## 106  4.110589710      4              2           4             0             2
## 107  2.774516966      3              3           3             0             0
## 108  1.643452676      2              2           2             0             0
## 109  2.450249108      3              3           3             0             0
## 110  1.804139432      2              2           2             0             0
## 111  0.342422681     NA             NA          NA            NA            NA
## 112  1.828015064      2              2           2             0             0
## 113  2.820857989      3              3           3             0             0
## 114  3.986771734      4              4           4             0             0
## 115  3.354108439      3              3           3             0             0
## 116  1.252853031      2              2           2             0             0
## 117  2.840733235      3              3           3             0             0
## 118  1.283301229      2              2           2             0             0
## 119  1.130333768     NA             NA          NA            NA            NA
## 120  2.301029996      2              2           2             0             0
## 121  3.056904851      3              3           3             0             0
## 122  2.359835482      2              2           2             0             0
## 123  0.359835482     NA             NA          NA            NA            NA
## 124  1.075546961      2              2           2             0             0
## 125  0.620136055     NA             NA          NA            NA            NA
## 126  0.271841607     NA             NA          NA            NA            NA
## 127  1.206825876      2              2           2             0             0
## 128  0.755112266      2              2           2             0             0
## 129  1.107209970      3              1           2            -1             2
## 130  1.240549248      3              3           3             0             0
## 131 -0.395773947      1              1           1             0             0
## 132 -0.094743951      2              2           2             0             0
## 133  0.980457892      2              2           2             0             0
## 134  0.994317153     NA             NA          NA            NA            NA
## 135  0.551449998      1              1           1             0             0
## 136  0.857935265      2              1           3             1             1
## 137  0.987666265      1              2           2             1            -1
## 138 -0.787812396     NA             NA          NA            NA            NA
## 139 -0.153044675      1              1           1             0             0
## 140  0.668385917     NA             NA          NA            NA            NA
## 141  0.930949031     NA             NA          NA            NA            NA
## 142  1.158362492      2              2           2             0             0
## 143  1.206825876      3              3           3             0             0
## 144  0.544068044      2              2           2             0             0
## 145  2.960946196      5              5           5             0             0
## 146  2.311753861      4              3           3            -1             1
## 147  0.176091259      2              2           2             0             0
## 148  2.079181246      3              3           3             0             0
## 149  2.204119983      3              1           3             0             2
## 150  1.100370545      2              2           2             0             0
## 151  0.110589710      1              1           1             0             0
## 152  1.392696953      4              4           4             0             0
## 153  0.708420900      0              0           1             1             0
## 154 -0.331614083      1              1           1             0             0
## 155  0.348304863      2              0           2             0             2
## 156  0.710963119      1              2           2             1            -1
## 157 -0.031984286     NA             NA          NA            NA            NA
## 158 -0.144480844      0              0           2             2             0
## 159 -0.204119983      0              0           0             0             0
## 160 -0.173277480      2              3           3             1            -1
## 161 -0.455931956      1              1           1             0             0
## 162  0.071882007      3              4           3             0            -1
## 163 -0.155522824      2              1           2             0             1
## 164 -0.118045029      2              3           3             1            -1
## 165  0.326335861      3              3           3             0             0
## 166 -0.196542884      1              1           2             1             0
## 167 -0.131355562      2              0           0            -2             2
## 168 -0.402304814      1              3           3             2            -2
## 169  0.260071388      3              1           3             0             2
## 170 -0.071604148      3              4           4             1            -1
## 171 -0.081445469      2              0           1            -1             2
## 172  0.459392488      3              3           3             0             0
## 173 -0.177178355      0              0           0             0             0
## 174 -0.077274542      0              0           0             0             0
## 175 -0.343901798      0              0           0             0             0
## 176 -0.661543506      0              2           2             2            -2
## 177 -0.368556231      1              1           1             0             0
## 178 -0.080398976      2              3           3             1            -1
## 179 -0.534617149      0              0           0             0             0
## 180 -0.151810883      1              3           3             2            -2
## 181 -0.090443971      0              0           0             0             0
## 182 -0.241845378      0              0           0             0             0
## 183 -0.542118103      0              0           0             0             0
## 184 -0.232844134      1              3           3             2            -2
## 185 -0.073657553      1              1           0            -1             0
## 186 -0.501689446      0              1           1             1            -1
## 187  0.037426498      2              1           1            -1             1
## 188 -0.059981845      0              0           2             2             0
## 189 -0.012333735     NA             NA          NA            NA            NA
## 190 -0.053056729      0              0           0             0             0
## 191  0.004321374      3              0           0            -3             3
## 192  0.235528447      2              4           4             2            -2
## 193  0.537819095      4              2           2            -2             2
## 194  0.017033339      3              4           4             1            -1
## 195  0.423245874      2              2           2             0             0
## 196  0.688419822      4              4           4             0             0
## 197 -0.095284455      0              0           0             0             0
## 198 -0.026872146      0              0           2             2             0
## 199  0.296665190      2              2           1            -1             0
## 200  0.523746467      3              4           4             1            -1
## 201  0.033423755      3              1           1            -2             2
## 202  0.457881897      2              1           2             0             1
## 203  0.542825427      2              3           3             1            -1
## 204 -0.093126465      0              0           0             0             0
## 205 -0.010995384     NA             NA          NA            NA            NA
## 206 -0.085656843      0              0           0             0             0
## 207  0.158362492      1              1           1             0             0
## 208  0.434568904      2              4           4             2            -2
## 209 -0.006123085      3              0           0            -3             3
## 210  0.334453751      1              1           1             0             0
## 211  0.610660163      3              2           2            -1             1
## 212 -0.069050969      0              0           1             1             0
## 213 -0.008773924     NA             NA          NA            NA            NA
## 214  0.212187604      1              1           1             0             0
## 215  0.488550717      2              2           2             0             0
## 216 -0.034798299      1              0           1             0             1
## 217  0.421603927     NA             NA          NA            NA            NA
## 218  0.582063363      2              1           2             0             1
## 219 -0.054039296     NA             NA          NA            NA            NA
## 220  0.056904851     NA             NA          NA            NA            NA
## 221  0.075546961      2              1           2             0             1
## 222 -0.083546051      1              1           0            -1             0
## 223 -0.024108864      2              2           2             0             0
## 224 -0.077274542      1              4           4             3            -3
## 225  0.734799830      4              6           6             2            -2
## 226  0.979092901      7              4           7             0             3
## 227 -0.144480844      2              0           4             2             2
## 228  0.737987326      4              4           4             0             0
## 229  0.975891136      5              5           6             1             0
## 230 -0.171340103      2              2           4             2             0
## 231  0.004321374      3              4           4             1            -1
## 232  0.758911892      4              2           3            -1             2
## 233  0.915927212      5              6           6             1            -1
## 234 -0.089375595      1              1           1             0             0
## 235  0.804139432      4              4           4             0             0
## 236  0.984527313      5              5           3            -2             0
## 237 -0.208309351      0              0           0             0             0
## 238  0.075546961      3              1           2            -1             2
## 239 -0.053547735      3              3           3             0             0
## 240  0.434568904      4              2           2            -2             2
## 241  0.598790507      3              6           5             2            -3
## 242  0.004321374      5              5           3            -2             0
## 243  0.374748346      2              3           4             2            -1
## 244  0.752048448      4              3           3            -1             1
## 245  0.004321374      3              3           4             1             0
## 246 -0.071604148      2              0           0            -2             2
## 247  0.396199347      2              4           4             2            -2
## 248  0.668385917      4              2           2            -2             2
## 249 -0.022733788      4              4           4             0             0
## 250  0.413299764      2              1           2             0             1
## 251  0.762678564      4              4           4             0             0
## 252 -0.029653124      2              2           0            -2             0
## 253  0.060697840      2              1           1            -1             1
## 254  0.033423755      2              1           0            -2             1
## 255  0.068185862      4              4           4             0             0
## 256  0.661812686      4              2           3            -1             2
## 257  0.874481818      6              6           6             0             0
## 258 -0.024108864      2              1           4             2             1
## 259  0.691081492      3              4           4             1            -1
## 260  0.831869774      4              4           4             0             0
## 261 -0.083546051      1              3           3             2            -2
## 262  0.041392685      2              0           1            -1             2
## 263  0.647382970      3              4           4             1            -1
## 264  0.867467488      5              4           2            -3             1
## 265  0.029383778      2              4           4             2            -2
## 266  0.736396502      3              3           3             0             0
## 267  0.848804701      4              4           3            -1             0
## 268 -0.076238039      1              1           0            -1             0
## 269 -0.016373713      0              1           2             2            -1
## 270 -0.181114585      0              0           0             0             0
## 271  0.530199698      2              4           4             2            -2
## 272  0.654176542      4              2           2            -2             2
## 273 -0.067019178      2              3           3             1            -1
## 274  0.564666064      2              2           2             0             0
## 275  0.712649702      3              4           4             1            -1
## 276 -0.034798299      2              0           0            -2             2
## 277 -0.151810883      0              1           2             2            -1
## 278  0.562292864      2              1           2             0             1
## 279  0.632457292      3              4           4             1            -1
## 280 -0.166215625      0              0           0             0             0
## 281  0.619093331      2              2           2             0             0
## 282  0.745074792      3              3           3             0             0
## 283 -0.040481623      1              1           0            -1             0
## 284 -0.071604148     NA             NA          NA            NA            NA
## 285 -0.013676223      1              0           1             0             1
## 286 -0.077274542      0              2           3             3            -2
## 287 -0.077274542      3              0           0            -3             3
## 288  0.459392488      4              3           4             0             1
## 289  0.636487896      4              4           6             2             0
## 290 -0.019088062      3              5           3             0            -2
## 291 -0.065501549      2              1           1            -1             1
## 292  0.521138084      3              5           2            -1            -2
## 293  0.113943352      2              0           1            -1             2
## 294 -0.155522824      1              3           3             2            -2
## 295  0.453318340      3              3           3             0             0
## 296  0.732393760      5              5           5             0             0
## 297 -0.107905397      2              0           0            -2             2
## 298  0.029383778      2              1           1            -1             1
## 299  0.526339277      4              2           2            -2             2
## 300 -0.010995384      1              3           3             2            -2
## 301 -0.074172425      0              1           0             0            -1
## 302 -0.166215625      1              2           2             1            -1
## 303 -0.208309351      1              1           0            -1             0
## 304  0.409933123      2              5           5             3            -3
## 305 -0.071604148      2              0           0            -2             2
## 306 -0.372634143      0              0           0             0             0
## 307  0.423245874      2              2           2             0             0
## 308  0.167317335      2              3           3             1            -1
## 309 -0.250263684      1              0           0            -1             1
## 310 -0.111259039      2              2           2             0             0
## 311  0.557507202      4              2           2            -2             2
## 312 -0.196542884      2              2           2             0             0
## 313 -0.327902142      0              1           1             1            -1
## 314  0.481442629      2              1           2             0             1
## 315  0.143014800      2              0           2             0             2
## 316 -0.012333735     NA             NA          NA            NA            NA
## 317  0.113943352      2              1           1            -1             1
## 318  0.103803721      2              3           3             1            -1
## 319  0.636487896      3              4           3             0            -1
## 320  0.868644438      5              5           2            -3             0
## 321  0.064457989      2              2           2             0             0
## 322  0.488550717      3              3           3             0             0
## 323  0.667452953      4              1           2            -2             3
## 324  0.245512668      3              3           3             0             0
## 325 -0.101823517      1              0           1             0             1
## 326  0.708420900      3              3           3             0             0
## 327  0.507855872      3              2           3             0             1
## 328 -0.065501549      2              2           2             0             0
## 329  0.463892989      1              1           2             1             0
## 330  0.503790683      2              3           2             0            -1
## 331  0.004321374      2              0           0            -2             2
## 332  0.021189299     NA             NA          NA            NA            NA
## 333 -0.141462802      1              1           0            -1             0
## 334  0.537819095      3              3           3             0             0
## 335  0.665580991      4              1           2            -2             3
## 336 -0.065501549      2              2           2             0             0
## 337  0.477121255      1              2           1             0            -1
## 338  0.654176542      3              3           3             0             0
## 339  0.209515015      2              1           1            -1             1
## 340 -0.301899454     NA             NA          NA            NA            NA
## 341  0.505149978      2              1           2             0             1
## 342  0.367355921      1              3           3             2            -2
## 343 -0.292429824      1              0           0            -1             1
## 344  0.480006943     NA             NA          NA            NA            NA
## 345  0.599883072      2              1           1            -1             1
## 346 -0.078313525     NA             NA          NA            NA            NA
## 347  0.056904851     NA             NA          NA            NA            NA
## 348  0.086359831      2              1           2             0             1
## 349  0.008600172      1              3           2             1            -2
## 350  0.029383778      2              1           2             0             1
## 351 -0.166215625      2              2           0            -2             0
## 352  0.979548375      5              6           6             1            -1
## 353  1.004321374      7              0           7             0             7
## 354  0.155336037      5              6           6             1            -1
## 355  0.935003151      5              3           2            -3             2
## 356  0.929929560      5              6           6             1            -1
## 357  0.723455672      5              0           2            -3             5
## 358 -0.173277480      0              0           0             0             0
## 359  0.941511433      5              5           2            -3             0
## 360  0.945468585      5              6           6             1            -1
## 361  0.103803721      4              0           0            -4             4
## 362  0.696356389      3              4           3             0            -1
## 363  0.836324116      4              1           1            -3             3
## 364  0.372912003      4              4           4             0             0
## 365  0.225309282      3              3           3             0             0
## 366 -0.101823517      3              1           1            -2             2
## 367  0.727541257      4              5           2            -2            -1
## 368  0.816903839      5              6           6             1            -1
## 369 -0.018634491      3              0           0            -3             3
## 370  0.627365857      3              3           4             1             0
## 371  0.851869601      5              0           2            -3             5
## 372  0.397940009      4              4           4             0             0
## 373 -0.118045029      2              2           2             0             0
## 374  0.705863712      3              4           4             1            -1
## 375  0.803457116      4              1           3            -1             3
## 376 -0.095284455      2              4           4             2            -2
## 377  0.582063363      2              1           2             0             1
## 378  0.824776462      4              4           4             0             0
## 379  0.313867220      3              1           1            -2             2
## 380  0.060697840      2              1           1            -1             1
## 381  0.146128036      2              3           3             1            -1
## 382 -0.224753740      1              0           1             0             1
## 383  1.000000000      5              1           1            -4             4
## 384  0.912753304      4              6           6             2            -2
## 385  0.107209970      4              0           0            -4             4
## 386  0.795880017      3              3           4             1             0
## 387  0.883093359      4              0           0            -4             4
## 388  0.359835482      4              4           4             0             0
## 389 -0.144480844      1              2           1             0            -1
## 390  0.649334859      1              4           4             3            -3
## 391  0.956648579      5              1           1            -4             4
## 392  0.021189299      3              4           4             1            -1
## 393  0.841359470      3              3           2            -1             0
## 394  0.918030337      4              4           4             0             0
## 395  0.278753601      3              1           1            -2             2
## 396  0.178976947      2              2           2             0             0
## 397 -0.287350298      0              2           2             2            -2
## 398  0.786751422      4              1           2            -2             3
## 399  0.800717078      5              1           1            -4             4
## 400  0.012837225      3              4           3             0            -1
## 401  0.745074792      3              3           3             0             0
## 402  0.602059991      1              4           4             3            -3
## 403  0.348304863      3              1           1            -2             2
## 404 -0.192464972      1              1           0            -1             0
## 405  0.720159303      3              3           3             0             0
## 406  0.758154622      4              4           4             0             0
## 407 -0.016373713      3              0           0            -3             3
## 408  0.671172843      2              2           2             0             0
## 409  0.742725131      3              1           1            -2             2
## 410 -0.449771647      0              1           1             1            -1
## 411  0.075546961     NA             NA          NA            NA            NA
## 412  0.264817823      2              1           1            -1             1
## 413 -0.019996628     NA             NA          NA            NA            NA
## 414  0.113943352     NA             NA          NA            NA            NA
## 415  0.045322979      0              2           2             2            -2
## 416  0.193124598      2              2           3             1             0
## 417  0.060697840      1              1           1             0             0
## 418  0.424881637      2              2           2             0             0
## 419  1.064457989      3              2           3             0             1
## 420  1.604226053      4              3           4             0             1
## 421  1.041392685      2              3           3             1            -1
## 422  0.356025857     NA             NA          NA            NA            NA
## 423  1.041392685      2              2           2             0             0
## 424  1.484299839      3              3           3             0             0
## 425  1.139879086      2              1           2             0             1
## 426  0.383815366     NA             NA          NA            NA            NA
## 427  0.416640507      2              1           2             0             1
## 428  0.938019097      3              3           2            -1             0
## 429  1.365487985      4              4           4             0             0
## 430  1.146128036      3              2           3             0             1
## 431  0.802773725      2              2           2             0             0
## 432  1.093421685      3              3           3             0             0
## 433  0.773054693      2              2           2             0             0
## 434 -0.012333735     NA             NA          NA            NA            NA
## 435  0.513217600      2              1           2             0             1
## 436  1.041392685      3              3           3             0             0
## 437  0.068185862      1              1           2             1             0
## 438  0.385606274     NA             NA          NA            NA            NA
## 439  0.770852012      2              2           2             0             0
## 440  0.139879086     NA             NA          NA            NA            NA
## 441  0.008600172     NA             NA          NA            NA            NA
## 442  0.195899652      1              2           1             0            -1
## 443  0.462397998      3              2           2            -1             1
## 444  0.691965103      3              3           3             0             0
## 445  1.012837225      4              4           4             0             0
## 446  0.755874856      3              3           3             0             0
## 447  0.332438460      2              2           2             0             0
## 448  0.238046103      2              0           1            -1             2
## 449  0.100370545      0              2           2             2            -2
## 450  0.017033339      2              1           2             0             1
## 451  0.374748346      2              2           2             0             0
## 452  0.764922985      3              3           3             0             0
## 453  0.146128036      2              2           3             1             0
## 454  0.149219113      1              2           1             0            -1
## 455  0.217483944      2              2           2             0             0
## 456  0.158362492      2              2           0            -2             0
## 457  0.086359831      2              1           2             0             1
## 458  0.472756449      2              2           2             0             0
## 459  0.758154622      3              3           3             0             0
## 460  0.997823081      4              5           5             1            -1
## 461  1.507855872      5              4           5             0             1
## 462  1.260071388      4              4           4             0             0
## 463  0.713490543      3              2           2            -1             1
## 464  1.322219295      4              5           4             0            -1
## 465  0.915399835      3              3           3             0             0
## 466  0.008600172      1              3           0            -1            -2
## 467  0.589949601      4              3           2            -2             1
## 468  0.898725182      4              5           5             1            -1
## 469  0.274157849      2              2           1            -1             0
## 470  0.570542940      3              2           3             0             1
## 471  0.840106094      3              2           3             0             1
## 472  0.365487985      2              3           3             1            -1
## 473 -0.008773924     NA             NA          NA            NA            NA
## 474  0.683947131      2              1           2             0             1
## 475  0.820201459      3              3           3             0             0
## 476  1.113943352      4              3           4             0             1
## 477  1.568201724      5              5           5             0             0
## 478  1.568201724      4              4           4             0             0
## 479  0.841984805      3              3           3             0             0
## 480  1.527629901      4              3           4             0             1
## 481  1.361727836      3              3           3             0             0
## 482 -0.014573526      0              0           0             0             0
## 483  0.478566496      1              3           1             0            -2
## 484  0.980003372      3              3           2            -1             0
## 485  0.281033367      2              2           2             0             0
## 486  0.539076099      2              1           2             0             1
## 487  0.898176483      3              3           3             0             0
## 488  0.380211242      2              1           2             0             1
## 489  0.004321374     NA             NA          NA            NA            NA
## 490  0.152288344      2              2           1            -1             0
## 491  0.621176282      3              3           3             0             0
## 492  0.611723308      2              4           4             2            -2
## 493  0.501059262      4              0           1            -3             4
## 494  0.376576957      2              3           4             2            -1
## 495  0.089905111      2              3           3             1            -1
## 496  0.243038049      3              4           4             1            -1
## 497  0.278753601      3              3           3             0             0
## 498  0.557507202      2              2           2             0             0
## 499  0.557507202      3              2           2            -1             1
## 500  0.460897843      2              4           4             2            -2
## 501  0.369215857      2              2           1            -1             0
## 502  0.004321374      1              2           0            -1            -1
## 503  0.110589710      3              0           0            -3             3
## 504 -0.031517051      0              2           2             2            -2
## 505  0.045322979     NA             NA          NA            NA            NA
## 506  0.506505032      2              2           1            -1             0
## 507  0.654176542      3              2           2            -1             1
## 508  0.442479769      1              4           4             3            -3
## 509  0.466867620      2              2           1            -1             0
## 510  0.086359831      2              2           2             0             0
## 511  0.170261715      3              3           2            -1             0
## 512  0.155336037      2              2           2             0             0
## 513  0.432969291     NA             NA          NA            NA            NA
## 514  0.403120521      1              2           2             1            -1
## 515  0.481442629      3              1           1            -2             2
## 516  0.352182518      1              2           1             0            -1
## 517  0.025305865     NA             NA          NA            NA            NA
## 518  0.033423755      1              2           2             1            -1
## 519  0.041392685     NA             NA          NA            NA            NA
## 520  0.056904851     NA             NA          NA            NA            NA
## 521  0.064457989      2              2           2             0             0
## 522 -0.008773924      0              3           2             2            -3
## 523  1.170261715      3              3           3             0             0
## 524  1.130333768      3              3           2            -1             0
## 525  1.212187604      4              6           4             0            -2
## 526  1.232996110      4              2           3            -1             2
## 527  0.117271296      3              0           2            -1             3
## 528  0.212187604      2              2           0            -2             0
## 529  0.269512944      3              4           4             1            -1
## 530  1.336459734      3              3           3             0             0
## 531  1.332438460      3              4           4             1            -1
## 532  1.276461804      3              2           2            -1             1
## 533  1.414973348      4              4           4             0             0
## 534 -0.006563770      0              0           0             0             0
## 535  0.053078443      1              4           2             1            -3
## 536  0.201397124      3              1           2            -1             2
## 537  0.133538908      2              2           0            -2             0
## 538  1.123851641      3              3           2            -1             0
## 539  1.093421685      3              4           4             1            -1
## 540  1.110589710      4              2           2            -2             2
## 541  0.967079734      2              4           4             2            -2
## 542  0.127104798      2              2           3             1             0
## 543  0.243038049      4              4           4             0             0
## 544  0.235528447      3              3           3             0             0
## 545  0.993876915      2              2           2             0             0
## 546  1.071882007      3              2           2            -1             1
## 547  1.217483944      4              4           4             0             0
## 548  1.149219113      3              2           2            -1             1
## 549  0.012837225      0              2           1             1            -2
## 550  0.075546961      3              0           0            -3             3
## 551  0.053078443      1              2           2             1            -1
## 552  0.613841822     NA             NA          NA            NA            NA
## 553  2.717670503      2              2           2             0             0
## 554  2.401400541      2              3           2             0            -1
## 555  2.799340549      3              3           2            -1             0
## 556  3.198657087      4              5           5             1            -1
## 557  2.999130541      1              1           1             0             0
## 558  3.107209970      5              5           5             0             0
## 559  3.240549248      4              2           1            -3             2
## 560  3.100370545      4              5           4             0            -1
## 561  2.831229694      4              2           2            -2             2
## 562  2.912222057      3              3           3             0             0
## 563  3.117271296      4              4           4             0             0
## 564  3.000000000      4              1           5             1             3
## 565  2.685741739      3              3           3             0             0
## 566  3.021189299      3              3           3             0             0
## 567  2.812244697      3              2           3             0             1
## 568  2.187520721      2              3           3             1            -1
## 569  0.572871602      1              1           1             0             0
## 570  0.570542940      1              3           3             2            -2
## 571  1.685741739      4              2           4             0             2
## 572  2.017033339      4              2           4             0             2
## 573  0.550228353      3              1           4             1             2
## 574  1.672097858      2              2           2             0             0
## 575  2.190331698      4              4           4             0             0
## 576  0.532754379      2              2           3             1             0
## 577  0.651278014      2              2           1            -1             0
## 578  1.664641976      2              2           2             0             0
## 579  0.474216264      0              3           1             1            -3
## 580  0.492760389      2              3           2             0            -1
## 581  1.951823035      2              2           2             0             0
## 582  1.367355921      2              2           2             0             0
## 583  0.481442629      1              1           1             0             0
## 584  0.820857989     NA             NA          NA            NA            NA
## 585  0.820201459      1              1           1             0             0
## 586  1.382017043      3              3           2            -1             0
## 587  2.950851459      4              4           3            -1             0
## 588  3.071882007      5              5           5             0             0
## 589  1.596597096      4              2           2            -2             2
## 590  2.113943352      2              3           2             0            -1
## 591  2.600972896      4              4           1            -3             0
## 592  0.945960704      2              3           1            -1            -1
## 593  1.267171728      2              2           2             0             0
## 594  2.725094521      3              3           3             0             0
## 595  2.634477270      3              4           4             1            -1
## 596  1.488550717      3              3           3             0             0
## 597  2.209515015      2              2           2             0             0
## 598  1.791690649      2              2           2             0             0
## 599  0.956648579      2              1           2             0             1
## 600 -0.193820026     NA             NA          NA            NA            NA
## 601  0.149219113      1              1           1             0             0
## 602  1.336459734      2              2           2             0             0
## 603  1.683047038      4              4           4             0             0
## 604  0.068185862      1              2           1             0            -1
## 605  1.235528447      1              1           2             1             0
## 606  1.630427875      3              1           2            -1             2
## 607 -0.194499142      0              0           2             2             0
## 608  0.274157849     NA             NA          NA            NA            NA
## 609  1.367355921      1              2           2             1            -1
## 610  1.158362492      2              2           2             0             0
## 611  0.371067862      2              1           1            -1             1
## 612  1.419955748     NA             NA          NA            NA            NA
## 613  0.691081492      1              1           1             0             0
## 614 -0.065501549     NA             NA          NA            NA            NA
## 615  0.178976947     NA             NA          NA            NA            NA
## 616  0.269512944      2              1           0            -2             1
## 617  3.611723308      3              3           3             0             0
## 618  3.611723308      2              2           2             0             0
## 619 -0.090979146     NA             NA          NA            NA            NA
## 620  2.561101384      2              1           2             0             1
## 621  1.201397124     NA             NA          NA            NA            NA
## 622  0.000000000     NA             NA          NA            NA            NA
## 623  1.201397124      2              1           2             0             1
## 624  0.962369336      1              3           3             2            -2
## 625  4.518513940      4              1           4             0             3
## 626  4.378397901      3              3           3             0             0
## 627  1.201397124      2              0           0            -2             2
## 628  3.611723308      3              3           3             0             0
## 629  2.416640507      2              2           2             0             0
## 630  0.000000000     NA             NA          NA            NA            NA
## 631  0.311753861      2              2           2             0             0
## 632  0.311753861      3              3           3             0             0
## 633  4.378397901      4              4           4             0             0
## 634  3.611723308      3              3           2            -1             0
## 635  0.000000000      2              0           0            -2             2
## 636  3.611723308      3              3           3             0             0
## 637  1.201397124      2              2           2             0             0
## 638  0.000000000      2              2           0            -2             0
## 639  1.371067862      3              3           3             0             0
## 640  1.201397124      3              0           3             0             3
## 641  4.668385917      5              4           5             0             1
## 642  4.285557309      3              4           4             1            -1
## 643  0.000000000      2              3           2             0            -1
## 644  3.611723308      4              4           4             0             0
## 645  3.611723308      3              2           3             0             1

What does accessibility look like in adaptive trajectories only?

adaptive_traj_access %>%
  filter(likely)
##    genotype           avg                               pos mutations likely
## 1    x0xx00 -0.1243552470                        p1|p26|p28         3   TRUE
## 2    00xx00  0.0301094048                           p26|p28         2   TRUE
## 3    000x00  1.8555191557                               p28         1   TRUE
## 4     xxxxx -0.4024022633               p21|p26|p28|p30|p94         5   TRUE
## 5     0xxxx  0.3612176043                   p26|p28|p30|p94         4   TRUE
## 6     0xx0x -0.0241508318                       p26|p28|p94         3   TRUE
## 7     00x00  1.1303337685                               p28         1   TRUE
## 8     00x0x  0.6093656589                           p28|p94         2   TRUE
## 9     xxxxx -0.4985709562               p21|p26|p28|p30|p94         5   TRUE
## 10    xxx0x -0.1734921898                   p21|p26|p28|p94         4   TRUE
## 11    0xx0x -0.0241508318                       p26|p28|p94         3   TRUE
## 12    00x00  1.1303337685                               p28         1   TRUE
## 13    00x0x  0.6093656589                           p28|p94         2   TRUE
## 14    0xx00 -0.0593328832                         p193|p258         2   TRUE
## 15    0xx0x  0.0001438909                    p193|p258|p273         3   TRUE
## 16    00x00  0.9943171527                              p258         1   TRUE
## 17    xxxxx -0.6987406300           p72|p193|p258|p271|p273         5   TRUE
## 18    xxx0x  0.2309903363                p72|p193|p258|p273         4   TRUE
## 19  00000x0  0.4216039269                              p225         1   TRUE
## 20  xxx00xx -0.2305882837           p41|p215|p219|p225|p227         5   TRUE
## 21  x0x00xx  0.0747386150                p41|p219|p225|p227         4   TRUE
## 22  x0000x0  0.1405845524                          p41|p225         2   TRUE
## 23  x0000xx  0.0088692029                     p41|p225|p227         3   TRUE
## 24  00000x0  0.4800069430                              p225         1   TRUE
## 25  xxxxxxx  1.9130554790 p41|p215|p219|p222|p224|p225|p227         7   TRUE
## 26  xxx0xxx -0.7393002155      p41|p215|p219|p224|p225|p227         6   TRUE
## 27  x0x0xxx  0.9140294387           p41|p219|p224|p225|p227         5   TRUE
## 28  x0x00x0  0.1701738576                     p41|p219|p225         3   TRUE
## 29  x0x00xx -0.5446666127                p41|p219|p225|p227         4   TRUE
## 30  x0000x0  0.1342610484                          p41|p225         2   TRUE
## 31     xxxx  0.2724234489                 p33|p72|p212|p213         4   TRUE
## 32     0x00  0.3560258572                               p72         1   TRUE
## 33     0xxx -0.5502135651                     p72|p212|p213         3   TRUE
## 34     0x0x  0.8038498576                          p72|p213         2   TRUE
## 35   00x0x0  0.0333520857                         p124|p156         2   TRUE
## 36   00x0xx -0.3439580192                    p124|p156|p243         3   TRUE
## 37   0000x0  0.3856062736                              p156         1   TRUE
## 38   xxxxxx  0.2371716121       p66|p76|p124|p132|p156|p243         6   TRUE
## 39   0xxxxx -0.1316049379           p76|p124|p132|p156|p243         5   TRUE
## 40   0xx0xx  0.3817071915                p76|p124|p156|p243         4   TRUE
## 41   000x00  0.4329692909                              p158         1   TRUE
## 42   xx0x00  0.2148131438                     p67|p142|p158         3   TRUE
## 43   xx0x0x -0.1873206652                p67|p142|p158|p215         4   TRUE
## 44   x00x00  0.5040027727                          p67|p158         2   TRUE
## 45   xxx0x0  0.8786927259               p233|p254|p271|p306         4   TRUE
## 46   xx00x0 -1.0031636940                    p233|p254|p306         3   TRUE
## 47   0x00x0 -0.0312987234                         p254|p306         2   TRUE
## 48   0000x0  1.4199557485                              p306         1   TRUE
## 49    00x0x  2.2313492364                         p104|p238         2   TRUE
## 50    0000x  1.2013971243                              p238         1   TRUE
## 51    0xxxx  1.9266775533                p42|p104|p182|p238         4   TRUE
## 52    0xx0x -1.4709889671                     p42|p104|p238         3   TRUE
## 53    xxxxx  0.2694733831          p4205|p42|p104|p182|p238         5   TRUE
##               unique_id enzyme_name measure_type      cond       means
## 1      DHFR_ic75_palmer        DHFR         ic75    palmer -0.37628762
## 2      DHFR_ic75_palmer        DHFR         ic75    palmer  0.51316879
## 3      DHFR_ic75_palmer        DHFR         ic75    palmer  0.02486007
## 4         DHFR_ki_trajg        DHFR           ki     trajg -0.40240226
## 5         DHFR_ki_trajg        DHFR           ki     trajg  0.16001647
## 6         DHFR_ki_trajg        DHFR           ki     trajg -0.03088869
## 7         DHFR_ki_trajg        DHFR           ki     trajg  1.39680945
## 8         DHFR_ki_trajg        DHFR           ki     trajg -0.29783448
## 9         DHFR_ki_trajr        DHFR           ki     trajr -0.49857096
## 10        DHFR_ki_trajr        DHFR           ki     trajr -0.42277767
## 11        DHFR_ki_trajr        DHFR           ki     trajr -0.45452917
## 12        DHFR_ki_trajr        DHFR           ki     trajr  1.55984210
## 13        DHFR_ki_trajr        DHFR           ki     trajr -0.07881130
## 14     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.04544503
## 15     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.13055704
## 16     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.64194186
## 17     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.69874063
## 18     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.11837998
## 19       NfsA_ec50_2039        NfsA         ec50      2039  0.47870667
## 20       NfsA_ec50_2039        NfsA         ec50      2039 -0.41197263
## 21       NfsA_ec50_2039        NfsA         ec50      2039 -0.03642342
## 22       NfsA_ec50_2039        NfsA         ec50      2039  0.53230784
## 23       NfsA_ec50_2039        NfsA         ec50      2039 -0.07627179
## 24       NfsA_ec50_3637        NfsA         ec50      3637  0.60053817
## 25       NfsA_ec50_3637        NfsA         ec50      3637  1.91305548
## 26       NfsA_ec50_3637        NfsA         ec50      3637  0.21722752
## 27       NfsA_ec50_3637        NfsA         ec50      3637  0.32566077
## 28       NfsA_ec50_3637        NfsA         ec50      3637 -0.04276810
## 29       NfsA_ec50_3637        NfsA         ec50      3637 -0.12431211
## 30       NfsA_ec50_3637        NfsA         ec50      3637  0.29847925
## 31 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.27242345
## 32 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.92788736
## 33 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.41400184
## 34 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.52980229
## 35 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.25754595
## 36 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.19574460
## 37 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.37836646
## 38 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.23717161
## 39 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.01301913
## 40 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.23085209
## 41 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.73061489
## 42 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.17401193
## 43 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.05144358
## 44 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.66294172
## 45       PTE_catact_2NH         PTE       catact       2NH -0.33352395
## 46       PTE_catact_2NH         PTE       catact       2NH -0.80218223
## 47       PTE_catact_2NH         PTE       catact       2NH -0.31271448
## 48       PTE_catact_2NH         PTE       catact       2NH  1.01057591
## 49    TEM_MIC_weinreich         TEM          MIC weinreich  0.81739780
## 50    TEM_MIC_weinreich         TEM          MIC weinreich  2.99832533
## 51    TEM_MIC_weinreich         TEM          MIC weinreich  2.06141424
## 52    TEM_MIC_weinreich         TEM          MIC weinreich -1.10269045
## 53    TEM_MIC_weinreich         TEM          MIC weinreich  0.26947338
##    traj_effects access access_no_idio access_mean access_w_mean access_w_idio
## 1     2.3424227      3              3           2            -1             0
## 2     2.1931246      2              2           2             0             0
## 3     1.8555192     NA             NA          NA            NA            NA
## 4     5.9656720      5              5           5             0             0
## 5     4.5820634      4              4           4             0             0
## 6     3.3541084      3              3           3             0             0
## 7     1.1303338     NA             NA          NA            NA            NA
## 8     2.3598355      2              2           2             0             0
## 9     5.2304489      5              5           5             0             0
## 10    4.2810334      4              4           4             0             0
## 11    3.3541084      3              3           3             0             0
## 12    1.1303338     NA             NA          NA            NA            NA
## 13    2.3598355      2              2           2             0             0
## 14    1.2068259      2              2           2             0             0
## 15    1.2405492      3              3           3             0             0
## 16    0.9943172     NA             NA          NA            NA            NA
## 17    2.9609462      5              5           5             0             0
## 18    2.3117539      4              3           3            -1             1
## 19    0.4216039     NA             NA          NA            NA            NA
## 20    0.9845273      5              5           3            -2             0
## 21    0.8488047      4              4           3            -1             0
## 22    0.6190933      2              2           2             0             0
## 23    0.7450748      3              3           3             0             0
## 24    0.4800069     NA             NA          NA            NA            NA
## 25    1.0043214      7              0           7             0             7
## 26    0.9454686      5              6           6             1            -1
## 27    0.9566486      5              1           1            -4             4
## 28    0.8413595      3              3           2            -1             0
## 29    0.9180303      4              4           4             0             0
## 30    0.6711728      2              2           2             0             0
## 31    1.6042261      4              3           4             0             1
## 32    0.3560259     NA             NA          NA            NA            NA
## 33    1.4842998      3              3           3             0             0
## 34    1.1398791      2              1           2             0             1
## 35    0.8027737      2              2           2             0             0
## 36    1.0934217      3              3           3             0             0
## 37    0.3856063     NA             NA          NA            NA            NA
## 38    1.5078559      5              4           5             0             1
## 39    1.5682017      5              5           5             0             0
## 40    1.5276299      4              3           4             0             1
## 41    0.4329693     NA             NA          NA            NA            NA
## 42    1.3364597      3              3           3             0             0
## 43    1.4149733      4              4           4             0             0
## 44    0.9938769      2              2           2             0             0
## 45    3.2405492      4              2           1            -3             2
## 46    3.0211893      3              3           3             0             0
## 47    2.2095150      2              2           2             0             0
## 48    1.4199557     NA             NA          NA            NA            NA
## 49    3.6117233      2              2           2             0             0
## 50    1.2013971     NA             NA          NA            NA            NA
## 51    4.5185139      4              1           4             0             3
## 52    4.3783979      3              3           3             0             0
## 53    4.6683859      5              4           5             0             1

And again for non-adaptive trajectories

adaptive_traj_access %>%
  filter(!likely)
##     genotype          avg                               pos mutations likely
## 1     x00000  0.643452676                                p1         1  FALSE
## 2     xx0000  0.012008907                            p1|p21         2  FALSE
## 3     xxx000  4.091500551                        p1|p21|p26         3  FALSE
## 4     xxxx00 -3.440073960                    p1|p21|p26|p28         4  FALSE
## 5     xxxxx0  0.212731913                p1|p21|p26|p28|p30         5  FALSE
## 6     xxxxxx -7.189135589            p1|p21|p26|p28|p30|p94         6  FALSE
## 7     xxxx0x 10.435863780                p1|p21|p26|p28|p94         5  FALSE
## 8     xxx0x0 -3.820446613                    p1|p21|p26|p30         4  FALSE
## 9     xxx0xx  2.575532781                p1|p21|p26|p30|p94         5  FALSE
## 10    xxx00x -5.302828501                    p1|p21|p26|p94         4  FALSE
## 11    xx0x00  0.793878371                        p1|p21|p28         3  FALSE
## 12    xx0xx0  1.995805108                    p1|p21|p28|p30         4  FALSE
## 13    xx0xxx  3.128986244                p1|p21|p28|p30|p94         5  FALSE
## 14    xx0x0x -5.214086328                    p1|p21|p28|p94         4  FALSE
## 15    xx00x0 -0.308921060                        p1|p21|p30         3  FALSE
## 16    xx00xx  1.369861023                    p1|p21|p30|p94         4  FALSE
## 17    xx000x  1.063593767                        p1|p21|p94         3  FALSE
## 18    x0x000  0.195179321                            p1|p26         2  FALSE
## 19    x0xxx0  0.256637693                    p1|p26|p28|p30         4  FALSE
## 20    x0xxxx  0.513576086                p1|p26|p28|p30|p94         5  FALSE
## 21    x0xx0x -1.104230472                    p1|p26|p28|p94         4  FALSE
## 22    x0x0x0 -0.580444171                        p1|p26|p30         3  FALSE
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## 578    x0000  0.000000000                             p4205         1  FALSE
## 579    x0x00  0.132776914                        p4205|p104         2  FALSE
## 580    x0xx0 -0.181515143                   p4205|p104|p182         3  FALSE
## 581    x0xxx -0.102432189              p4205|p104|p182|p238         4  FALSE
## 582    x0x0x -0.132776914                   p4205|p104|p238         3  FALSE
## 583    x00x0  0.090979146                        p4205|p182         2  FALSE
## 584    x00xx  0.959642779                   p4205|p182|p238         3  FALSE
## 585    x000x  0.000000000                        p4205|p238         2  FALSE
## 586    xx000  0.000000000                         p4205|p42         2  FALSE
## 587    xxx00  0.036893824                    p4205|p42|p104         3  FALSE
## 588    xxxx0  1.452269318               p4205|p42|p104|p182         4  FALSE
## 589    xxx0x -1.324817217               p4205|p42|p104|p238         4  FALSE
## 590    xx0x0 -1.292376270                    p4205|p42|p182         3  FALSE
## 591    xx0xx -0.953328455               p4205|p42|p182|p238         4  FALSE
## 592    xx00x  1.195082801                    p4205|p42|p238         3  FALSE
##                unique_id enzyme_name measure_type      cond         means
## 1       DHFR_ic75_palmer        DHFR         ic75    palmer  1.2062354930
## 2       DHFR_ic75_palmer        DHFR         ic75    palmer  0.8239107693
## 3       DHFR_ic75_palmer        DHFR         ic75    palmer  0.2172161842
## 4       DHFR_ic75_palmer        DHFR         ic75    palmer  0.0869399897
## 5       DHFR_ic75_palmer        DHFR         ic75    palmer -3.3818358819
## 6       DHFR_ic75_palmer        DHFR         ic75    palmer -7.1891355892
## 7       DHFR_ic75_palmer        DHFR         ic75    palmer  6.8412959859
## 8       DHFR_ic75_palmer        DHFR         ic75    palmer -4.2235981639
## 9       DHFR_ic75_palmer        DHFR         ic75    palmer -1.0190350137
## 10      DHFR_ic75_palmer        DHFR         ic75    palmer -0.5944141171
## 11      DHFR_ic75_palmer        DHFR         ic75    palmer  0.0104543165
## 12      DHFR_ic75_palmer        DHFR         ic75    palmer  1.8693802891
## 13      DHFR_ic75_palmer        DHFR         ic75    palmer -0.4655815508
## 14      DHFR_ic75_palmer        DHFR         ic75    palmer -0.2289452136
## 15      DHFR_ic75_palmer        DHFR         ic75    palmer  0.0443594841
## 16      DHFR_ic75_palmer        DHFR         ic75    palmer  2.4248366377
## 17      DHFR_ic75_palmer        DHFR         ic75    palmer -0.3734793838
## 18      DHFR_ic75_palmer        DHFR         ic75    palmer  0.2155007877
## 19      DHFR_ic75_palmer        DHFR         ic75    palmer -1.1774922053
## 20      DHFR_ic75_palmer        DHFR         ic75    palmer -3.0809917088
## 21      DHFR_ic75_palmer        DHFR         ic75    palmer  2.5732055642
## 22      DHFR_ic75_palmer        DHFR         ic75    palmer -2.3319717766
## 23      DHFR_ic75_palmer        DHFR         ic75    palmer -0.0456122478
## 24      DHFR_ic75_palmer        DHFR         ic75    palmer  0.1027002613
## 25      DHFR_ic75_palmer        DHFR         ic75    palmer  0.1307275253
## 26      DHFR_ic75_palmer        DHFR         ic75    palmer  1.9214364729
## 27      DHFR_ic75_palmer        DHFR         ic75    palmer  2.2547035770
## 28      DHFR_ic75_palmer        DHFR         ic75    palmer  1.6478415588
## 29      DHFR_ic75_palmer        DHFR         ic75    palmer  0.6951950425
## 30      DHFR_ic75_palmer        DHFR         ic75    palmer  1.7901616616
## 31      DHFR_ic75_palmer        DHFR         ic75    palmer  0.1627485133
## 32      DHFR_ic75_palmer        DHFR         ic75    palmer -0.6411418079
## 33      DHFR_ic75_palmer        DHFR         ic75    palmer  0.5351546470
## 34      DHFR_ic75_palmer        DHFR         ic75    palmer  1.1245241043
## 35      DHFR_ic75_palmer        DHFR         ic75    palmer -1.3228789457
## 36      DHFR_ic75_palmer        DHFR         ic75    palmer -2.6399845605
## 37      DHFR_ic75_palmer        DHFR         ic75    palmer -0.8278135882
## 38      DHFR_ic75_palmer        DHFR         ic75    palmer  0.9472975263
## 39      DHFR_ic75_palmer        DHFR         ic75    palmer -1.8621430146
## 40      DHFR_ic75_palmer        DHFR         ic75    palmer  1.6952992211
## 41      DHFR_ic75_palmer        DHFR         ic75    palmer -0.9917867991
## 42      DHFR_ic75_palmer        DHFR         ic75    palmer  0.7602580277
## 43      DHFR_ic75_palmer        DHFR         ic75    palmer  2.8704376498
## 44      DHFR_ic75_palmer        DHFR         ic75    palmer -0.8496609691
## 45      DHFR_ic75_palmer        DHFR         ic75    palmer  0.2988833330
## 46      DHFR_ic75_palmer        DHFR         ic75    palmer  0.2794516133
## 47      DHFR_ic75_palmer        DHFR         ic75    palmer -0.6590651019
## 48      DHFR_ic75_palmer        DHFR         ic75    palmer  0.4601334499
## 49      DHFR_ic75_palmer        DHFR         ic75    palmer -0.8931744546
## 50      DHFR_ic75_palmer        DHFR         ic75    palmer -0.9737236775
## 51      DHFR_ic75_palmer        DHFR         ic75    palmer -0.0430876032
## 52      DHFR_ic75_palmer        DHFR         ic75    palmer  0.3528148943
## 53      DHFR_ic75_palmer        DHFR         ic75    palmer -1.0887019893
## 54      DHFR_ic75_palmer        DHFR         ic75    palmer  0.4966773128
## 55      DHFR_ic75_palmer        DHFR         ic75    palmer -0.6911103475
## 56      DHFR_ic75_palmer        DHFR         ic75    palmer  0.6800591798
## 57      DHFR_ic75_palmer        DHFR         ic75    palmer -1.8036554355
## 58      DHFR_ic75_palmer        DHFR         ic75    palmer  0.1999543556
## 59      DHFR_ic75_palmer        DHFR         ic75    palmer -0.5632148850
## 60      DHFR_ic75_palmer        DHFR         ic75    palmer -0.1737197244
## 61         DHFR_ki_trajg        DHFR           ki     trajg  0.9697491865
## 62         DHFR_ki_trajg        DHFR           ki     trajg  0.4109127529
## 63         DHFR_ki_trajg        DHFR           ki     trajg  0.0820066602
## 64         DHFR_ki_trajg        DHFR           ki     trajg -0.3698938721
## 65         DHFR_ki_trajg        DHFR           ki     trajg -0.3746933214
## 66         DHFR_ki_trajg        DHFR           ki     trajg -0.1078647001
## 67         DHFR_ki_trajg        DHFR           ki     trajg  0.3260605832
## 68         DHFR_ki_trajg        DHFR           ki     trajg  0.0776194738
## 69         DHFR_ki_trajg        DHFR           ki     trajg  0.0773038378
## 70         DHFR_ki_trajg        DHFR           ki     trajg  0.4387885429
## 71         DHFR_ki_trajg        DHFR           ki     trajg  1.6725909180
## 72         DHFR_ki_trajg        DHFR           ki     trajg -0.2379599604
## 73         DHFR_ki_trajg        DHFR           ki     trajg  0.2140346062
## 74         DHFR_ki_trajg        DHFR           ki     trajg -0.5594039435
## 75         DHFR_ki_trajg        DHFR           ki     trajg  0.0156588163
## 76         DHFR_ki_trajg        DHFR           ki     trajg  1.1162865010
## 77         DHFR_ki_trajg        DHFR           ki     trajg  0.4024060198
## 78         DHFR_ki_trajg        DHFR           ki     trajg -0.1485079546
## 79         DHFR_ki_trajg        DHFR           ki     trajg  0.4189568454
## 80         DHFR_ki_trajg        DHFR           ki     trajg -0.0180350968
## 81         DHFR_ki_trajg        DHFR           ki     trajg  0.2569441197
## 82         DHFR_ki_trajg        DHFR           ki     trajg -0.2775070636
## 83         DHFR_ki_trajg        DHFR           ki     trajg -0.7159940330
## 84         DHFR_ki_trajg        DHFR           ki     trajg  1.3184002269
## 85         DHFR_ki_trajg        DHFR           ki     trajg  0.5356077160
## 86         DHFR_ki_trajg        DHFR           ki     trajg  1.4946366750
## 87         DHFR_ki_trajr        DHFR           ki     trajr  0.9837809276
## 88         DHFR_ki_trajr        DHFR           ki     trajr  0.2391675950
## 89         DHFR_ki_trajr        DHFR           ki     trajr  0.4455707916
## 90         DHFR_ki_trajr        DHFR           ki     trajr  0.3572343908
## 91         DHFR_ki_trajr        DHFR           ki     trajr -0.4513550160
## 92         DHFR_ki_trajr        DHFR           ki     trajr  0.1502588862
## 93         DHFR_ki_trajr        DHFR           ki     trajr -0.0102813748
## 94         DHFR_ki_trajr        DHFR           ki     trajr -0.1460729622
## 95         DHFR_ki_trajr        DHFR           ki     trajr -0.0079650572
## 96         DHFR_ki_trajr        DHFR           ki     trajr  1.0204882392
## 97         DHFR_ki_trajr        DHFR           ki     trajr -0.5640112998
## 98         DHFR_ki_trajr        DHFR           ki     trajr  0.2420980885
## 99         DHFR_ki_trajr        DHFR           ki     trajr -0.0307196048
## 100        DHFR_ki_trajr        DHFR           ki     trajr  0.2800009857
## 101        DHFR_ki_trajr        DHFR           ki     trajr  0.9702638982
## 102        DHFR_ki_trajr        DHFR           ki     trajr  0.0922497590
## 103        DHFR_ki_trajr        DHFR           ki     trajr -0.7688204762
## 104        DHFR_ki_trajr        DHFR           ki     trajr -0.6872644817
## 105        DHFR_ki_trajr        DHFR           ki     trajr  0.1269116399
## 106        DHFR_ki_trajr        DHFR           ki     trajr  0.4075661730
## 107        DHFR_ki_trajr        DHFR           ki     trajr  0.4697447546
## 108        DHFR_ki_trajr        DHFR           ki     trajr  0.0485582393
## 109        DHFR_ki_trajr        DHFR           ki     trajr -0.2779476645
## 110        DHFR_ki_trajr        DHFR           ki     trajr  0.9680966144
## 111        DHFR_ki_trajr        DHFR           ki     trajr -0.0381671545
## 112        DHFR_ki_trajr        DHFR           ki     trajr  1.2077492397
## 113     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6014530846
## 114     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.0262381099
## 115     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.0298359555
## 116     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.0829901928
## 117     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.1933522503
## 118     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6141302903
## 119     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.5759713003
## 120     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.5753711677
## 121     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.0779951552
## 122     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.4725758154
## 123     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6166938011
## 124     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6761999762
## 125     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.5888533443
## 126     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.7147608105
## 127     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.0329280268
## 128     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.1735958962
## 129     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.2389949571
## 130     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.0179745831
## 131     MPH_catact_ZnPTM         MPH       catact     ZnPTM  1.3320209103
## 132     MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.5190551772
## 133     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.0547379301
## 134     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.0780273638
## 135     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6575819217
## 136     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.1822762261
## 137     MPH_catact_ZnPTM         MPH       catact     ZnPTM  1.1382346025
## 138     MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.6027861091
## 139       NfsA_ec50_2039        NfsA         ec50      2039 -0.1836051261
## 140       NfsA_ec50_2039        NfsA         ec50      2039  0.0681046216
## 141       NfsA_ec50_2039        NfsA         ec50      2039 -0.0186503117
## 142       NfsA_ec50_2039        NfsA         ec50      2039 -0.0062579777
## 143       NfsA_ec50_2039        NfsA         ec50      2039  0.0916418075
## 144       NfsA_ec50_2039        NfsA         ec50      2039 -0.1062233107
## 145       NfsA_ec50_2039        NfsA         ec50      2039  0.0752331625
## 146       NfsA_ec50_2039        NfsA         ec50      2039 -0.0067424598
## 147       NfsA_ec50_2039        NfsA         ec50      2039 -0.0365279925
## 148       NfsA_ec50_2039        NfsA         ec50      2039  0.0386176943
## 149       NfsA_ec50_2039        NfsA         ec50      2039 -0.0364612571
## 150       NfsA_ec50_2039        NfsA         ec50      2039 -0.1043226875
## 151       NfsA_ec50_2039        NfsA         ec50      2039  0.2455043396
## 152       NfsA_ec50_2039        NfsA         ec50      2039 -0.0039551835
## 153       NfsA_ec50_2039        NfsA         ec50      2039  0.3517777861
## 154       NfsA_ec50_2039        NfsA         ec50      2039  0.0709342958
## 155       NfsA_ec50_2039        NfsA         ec50      2039 -0.0105120513
## 156       NfsA_ec50_2039        NfsA         ec50      2039 -0.0298045492
## 157       NfsA_ec50_2039        NfsA         ec50      2039 -0.0255586573
## 158       NfsA_ec50_2039        NfsA         ec50      2039  0.0695594275
## 159       NfsA_ec50_2039        NfsA         ec50      2039  0.0428042028
## 160       NfsA_ec50_2039        NfsA         ec50      2039  0.0337737283
## 161       NfsA_ec50_2039        NfsA         ec50      2039 -0.0359432925
## 162       NfsA_ec50_2039        NfsA         ec50      2039 -0.0903033454
## 163       NfsA_ec50_2039        NfsA         ec50      2039 -0.0556827046
## 164       NfsA_ec50_2039        NfsA         ec50      2039 -0.0281368788
## 165       NfsA_ec50_2039        NfsA         ec50      2039 -0.0177819590
## 166       NfsA_ec50_2039        NfsA         ec50      2039 -0.1324799126
## 167       NfsA_ec50_2039        NfsA         ec50      2039 -0.0358644364
## 168       NfsA_ec50_2039        NfsA         ec50      2039 -0.2410580287
## 169       NfsA_ec50_2039        NfsA         ec50      2039  0.1397653277
## 170       NfsA_ec50_2039        NfsA         ec50      2039  0.0963359828
## 171       NfsA_ec50_2039        NfsA         ec50      2039  0.1058026609
## 172       NfsA_ec50_2039        NfsA         ec50      2039  0.0075018912
## 173       NfsA_ec50_2039        NfsA         ec50      2039 -0.0220382404
## 174       NfsA_ec50_2039        NfsA         ec50      2039  0.0328627091
## 175       NfsA_ec50_2039        NfsA         ec50      2039  0.0912835621
## 176       NfsA_ec50_2039        NfsA         ec50      2039 -0.0629425668
## 177       NfsA_ec50_2039        NfsA         ec50      2039  0.0346434105
## 178       NfsA_ec50_2039        NfsA         ec50      2039  0.0975715483
## 179       NfsA_ec50_2039        NfsA         ec50      2039 -0.0173590203
## 180       NfsA_ec50_2039        NfsA         ec50      2039  0.0653162028
## 181       NfsA_ec50_2039        NfsA         ec50      2039 -0.1337930941
## 182       NfsA_ec50_2039        NfsA         ec50      2039  0.2123040146
## 183       NfsA_ec50_2039        NfsA         ec50      2039  0.0339294274
## 184       NfsA_ec50_2039        NfsA         ec50      2039  0.2326842483
## 185       NfsA_ec50_2039        NfsA         ec50      2039  0.0906688737
## 186       NfsA_ec50_2039        NfsA         ec50      2039 -0.0193446645
## 187       NfsA_ec50_2039        NfsA         ec50      2039 -0.0274577404
## 188       NfsA_ec50_2039        NfsA         ec50      2039 -0.0044199260
## 189       NfsA_ec50_2039        NfsA         ec50      2039  0.0062850048
## 190       NfsA_ec50_2039        NfsA         ec50      2039 -0.0280033491
## 191       NfsA_ec50_2039        NfsA         ec50      2039 -0.0146378985
## 192       NfsA_ec50_2039        NfsA         ec50      2039 -0.0229229906
## 193       NfsA_ec50_2039        NfsA         ec50      2039 -0.0166336540
## 194       NfsA_ec50_2039        NfsA         ec50      2039  0.0163758077
## 195       NfsA_ec50_2039        NfsA         ec50      2039 -0.0629292093
## 196       NfsA_ec50_2039        NfsA         ec50      2039 -0.0978057282
## 197       NfsA_ec50_2039        NfsA         ec50      2039 -0.1077205690
## 198       NfsA_ec50_2039        NfsA         ec50      2039  0.0521695212
## 199       NfsA_ec50_2039        NfsA         ec50      2039  0.2889894811
## 200       NfsA_ec50_2039        NfsA         ec50      2039  0.1275384125
## 201       NfsA_ec50_2039        NfsA         ec50      2039  0.3094435780
## 202       NfsA_ec50_2039        NfsA         ec50      2039  0.3579534467
## 203       NfsA_ec50_2039        NfsA         ec50      2039 -0.1455269649
## 204       NfsA_ec50_2039        NfsA         ec50      2039  0.0204132770
## 205       NfsA_ec50_2039        NfsA         ec50      2039 -0.0004683640
## 206       NfsA_ec50_2039        NfsA         ec50      2039  0.0200263949
## 207       NfsA_ec50_2039        NfsA         ec50      2039  0.2315052064
## 208       NfsA_ec50_2039        NfsA         ec50      2039  0.3065119830
## 209       NfsA_ec50_2039        NfsA         ec50      2039  0.0355119615
## 210       NfsA_ec50_2039        NfsA         ec50      2039  0.1239119618
## 211       NfsA_ec50_2039        NfsA         ec50      2039  0.1770238631
## 212       NfsA_ec50_2039        NfsA         ec50      2039 -0.0211872665
## 213       NfsA_ec50_2039        NfsA         ec50      2039  0.2825320265
## 214       NfsA_ec50_2039        NfsA         ec50      2039 -0.3709280451
## 215       NfsA_ec50_2039        NfsA         ec50      2039 -0.0382235176
## 216       NfsA_ec50_2039        NfsA         ec50      2039 -0.0089850783
## 217       NfsA_ec50_2039        NfsA         ec50      2039 -0.1245892565
## 218       NfsA_ec50_2039        NfsA         ec50      2039  0.0745672884
## 219       NfsA_ec50_2039        NfsA         ec50      2039 -0.0478116786
## 220       NfsA_ec50_2039        NfsA         ec50      2039  0.0303642996
## 221       NfsA_ec50_2039        NfsA         ec50      2039 -0.2624441094
## 222       NfsA_ec50_2039        NfsA         ec50      2039 -0.0812688215
## 223       NfsA_ec50_2039        NfsA         ec50      2039  0.0529152655
## 224       NfsA_ec50_2039        NfsA         ec50      2039  0.2146652139
## 225       NfsA_ec50_2039        NfsA         ec50      2039  0.0783215107
## 226       NfsA_ec50_2039        NfsA         ec50      2039  0.0891218831
## 227       NfsA_ec50_2039        NfsA         ec50      2039 -0.0297717435
## 228       NfsA_ec50_2039        NfsA         ec50      2039  0.0468898238
## 229       NfsA_ec50_2039        NfsA         ec50      2039 -0.0227298126
## 230       NfsA_ec50_2039        NfsA         ec50      2039  0.5286519492
## 231       NfsA_ec50_2039        NfsA         ec50      2039 -0.0403094169
## 232       NfsA_ec50_2039        NfsA         ec50      2039 -0.1051249211
## 233       NfsA_ec50_2039        NfsA         ec50      2039  0.0073342133
## 234       NfsA_ec50_2039        NfsA         ec50      2039 -0.0252371270
## 235       NfsA_ec50_2039        NfsA         ec50      2039 -0.0236105839
## 236       NfsA_ec50_2039        NfsA         ec50      2039  0.1727504818
## 237       NfsA_ec50_2039        NfsA         ec50      2039 -0.0086689450
## 238       NfsA_ec50_2039        NfsA         ec50      2039  0.1369784273
## 239       NfsA_ec50_2039        NfsA         ec50      2039  0.0017264238
## 240       NfsA_ec50_2039        NfsA         ec50      2039  0.0432167804
## 241       NfsA_ec50_2039        NfsA         ec50      2039  0.0005318277
## 242       NfsA_ec50_2039        NfsA         ec50      2039  0.0516320608
## 243       NfsA_ec50_2039        NfsA         ec50      2039  0.0512407834
## 244       NfsA_ec50_2039        NfsA         ec50      2039 -0.0392870444
## 245       NfsA_ec50_2039        NfsA         ec50      2039  0.0058148649
## 246       NfsA_ec50_2039        NfsA         ec50      2039  0.0040635316
## 247       NfsA_ec50_2039        NfsA         ec50      2039 -0.0651786412
## 248       NfsA_ec50_2039        NfsA         ec50      2039  0.0377675481
## 249       NfsA_ec50_2039        NfsA         ec50      2039  0.0357611152
## 250       NfsA_ec50_2039        NfsA         ec50      2039  0.0795724700
## 251       NfsA_ec50_2039        NfsA         ec50      2039  0.0143172459
## 252       NfsA_ec50_2039        NfsA         ec50      2039 -0.0049343146
## 253       NfsA_ec50_2039        NfsA         ec50      2039  0.0165982946
## 254       NfsA_ec50_2039        NfsA         ec50      2039  0.0251150682
## 255       NfsA_ec50_2039        NfsA         ec50      2039  0.0117068309
## 256       NfsA_ec50_2039        NfsA         ec50      2039  0.0584999147
## 257       NfsA_ec50_2039        NfsA         ec50      2039  0.1708262589
## 258       NfsA_ec50_2039        NfsA         ec50      2039 -0.0262790812
## 259       NfsA_ec50_2039        NfsA         ec50      2039 -0.0353591048
## 260       NfsA_ec50_2039        NfsA         ec50      2039 -0.1138374545
## 261       NfsA_ec50_3637        NfsA         ec50      3637 -0.0569706652
## 262       NfsA_ec50_3637        NfsA         ec50      3637  0.0207202924
## 263       NfsA_ec50_3637        NfsA         ec50      3637  0.0617297495
## 264       NfsA_ec50_3637        NfsA         ec50      3637 -0.1321747554
## 265       NfsA_ec50_3637        NfsA         ec50      3637  0.2251203280
## 266       NfsA_ec50_3637        NfsA         ec50      3637  0.9181359551
## 267       NfsA_ec50_3637        NfsA         ec50      3637 -0.2032811849
## 268       NfsA_ec50_3637        NfsA         ec50      3637 -0.0733541727
## 269       NfsA_ec50_3637        NfsA         ec50      3637 -0.3954314003
## 270       NfsA_ec50_3637        NfsA         ec50      3637  0.1603000840
## 271       NfsA_ec50_3637        NfsA         ec50      3637  0.0692931523
## 272       NfsA_ec50_3637        NfsA         ec50      3637  0.0172715963
## 273       NfsA_ec50_3637        NfsA         ec50      3637 -0.2790421770
## 274       NfsA_ec50_3637        NfsA         ec50      3637  0.0926146264
## 275       NfsA_ec50_3637        NfsA         ec50      3637  0.2187172032
## 276       NfsA_ec50_3637        NfsA         ec50      3637 -0.2894908905
## 277       NfsA_ec50_3637        NfsA         ec50      3637 -0.1314996851
## 278       NfsA_ec50_3637        NfsA         ec50      3637 -0.0734456760
## 279       NfsA_ec50_3637        NfsA         ec50      3637 -0.0248115637
## 280       NfsA_ec50_3637        NfsA         ec50      3637 -0.2871770486
## 281       NfsA_ec50_3637        NfsA         ec50      3637 -0.1946197462
## 282       NfsA_ec50_3637        NfsA         ec50      3637  0.0122059190
## 283       NfsA_ec50_3637        NfsA         ec50      3637  0.0057623657
## 284       NfsA_ec50_3637        NfsA         ec50      3637  0.0236221014
## 285       NfsA_ec50_3637        NfsA         ec50      3637 -0.0741606229
## 286       NfsA_ec50_3637        NfsA         ec50      3637  0.0225808245
## 287       NfsA_ec50_3637        NfsA         ec50      3637  0.1432529308
## 288       NfsA_ec50_3637        NfsA         ec50      3637  0.1044974531
## 289       NfsA_ec50_3637        NfsA         ec50      3637 -0.1794361674
## 290       NfsA_ec50_3637        NfsA         ec50      3637 -0.1712352281
## 291       NfsA_ec50_3637        NfsA         ec50      3637  0.1681112032
## 292       NfsA_ec50_3637        NfsA         ec50      3637  0.1876979101
## 293       NfsA_ec50_3637        NfsA         ec50      3637  0.1242066126
## 294       NfsA_ec50_3637        NfsA         ec50      3637  0.0060707290
## 295       NfsA_ec50_3637        NfsA         ec50      3637  0.0273060835
## 296       NfsA_ec50_3637        NfsA         ec50      3637 -0.0580679126
## 297       NfsA_ec50_3637        NfsA         ec50      3637 -0.1621399356
## 298       NfsA_ec50_3637        NfsA         ec50      3637 -0.0461866784
## 299       NfsA_ec50_3637        NfsA         ec50      3637  0.0826201157
## 300       NfsA_ec50_3637        NfsA         ec50      3637  0.0611866980
## 301       NfsA_ec50_3637        NfsA         ec50      3637 -0.0234087043
## 302       NfsA_ec50_3637        NfsA         ec50      3637  0.0748541626
## 303       NfsA_ec50_3637        NfsA         ec50      3637  0.0553774954
## 304       NfsA_ec50_3637        NfsA         ec50      3637  0.0922134343
## 305       NfsA_ec50_3637        NfsA         ec50      3637 -0.0564313255
## 306       NfsA_ec50_3637        NfsA         ec50      3637  0.0927015930
## 307       NfsA_ec50_3637        NfsA         ec50      3637 -0.1914053813
## 308       NfsA_ec50_3637        NfsA         ec50      3637  0.0034482452
## 309       NfsA_ec50_3637        NfsA         ec50      3637  0.0743519850
## 310       NfsA_ec50_3637        NfsA         ec50      3637 -0.0222180181
## 311       NfsA_ec50_3637        NfsA         ec50      3637  0.1118174567
## 312       NfsA_ec50_3637        NfsA         ec50      3637  0.1675711646
## 313       NfsA_ec50_3637        NfsA         ec50      3637 -0.0544554698
## 314       NfsA_ec50_3637        NfsA         ec50      3637 -0.0782406699
## 315       NfsA_ec50_3637        NfsA         ec50      3637 -0.1210110456
## 316       NfsA_ec50_3637        NfsA         ec50      3637  0.0633115530
## 317       NfsA_ec50_3637        NfsA         ec50      3637 -0.0562297539
## 318       NfsA_ec50_3637        NfsA         ec50      3637  0.3126121933
## 319       NfsA_ec50_3637        NfsA         ec50      3637 -0.0750305493
## 320       NfsA_ec50_3637        NfsA         ec50      3637 -0.0653991572
## 321       NfsA_ec50_3637        NfsA         ec50      3637  0.0523536890
## 322       NfsA_ec50_3637        NfsA         ec50      3637  0.1660586859
## 323       NfsA_ec50_3637        NfsA         ec50      3637  0.2481057780
## 324       NfsA_ec50_3637        NfsA         ec50      3637  0.2334684124
## 325       NfsA_ec50_3637        NfsA         ec50      3637 -0.0902993257
## 326       NfsA_ec50_3637        NfsA         ec50      3637  0.1100160218
## 327       NfsA_ec50_3637        NfsA         ec50      3637 -0.4441508278
## 328       NfsA_ec50_3637        NfsA         ec50      3637  0.1480407335
## 329       NfsA_ec50_3637        NfsA         ec50      3637  0.0349365724
## 330       NfsA_ec50_3637        NfsA         ec50      3637 -0.1825827093
## 331       NfsA_ec50_3637        NfsA         ec50      3637 -0.1683354659
## 332       NfsA_ec50_3637        NfsA         ec50      3637  0.2066348605
## 333       NfsA_ec50_3637        NfsA         ec50      3637  0.1466547909
## 334       NfsA_ec50_3637        NfsA         ec50      3637 -0.0751033646
## 335       NfsA_ec50_3637        NfsA         ec50      3637  0.2265367060
## 336       NfsA_ec50_3637        NfsA         ec50      3637 -0.2405484081
## 337       NfsA_ec50_3637        NfsA         ec50      3637 -0.0482498806
## 338       NfsA_ec50_3637        NfsA         ec50      3637  0.1296145456
## 339       NfsA_ec50_3637        NfsA         ec50      3637  0.1452661161
## 340       NfsA_ec50_3637        NfsA         ec50      3637  0.0166145089
## 341       NfsA_ec50_3637        NfsA         ec50      3637 -0.1953665691
## 342       NfsA_ec50_3637        NfsA         ec50      3637  0.5683588741
## 343       NfsA_ec50_3637        NfsA         ec50      3637  0.2764296357
## 344       NfsA_ec50_3637        NfsA         ec50      3637  0.1256842504
## 345       NfsA_ec50_3637        NfsA         ec50      3637  0.4798621280
## 346       NfsA_ec50_3637        NfsA         ec50      3637  0.1207426029
## 347       NfsA_ec50_3637        NfsA         ec50      3637 -0.1216801227
## 348       NfsA_ec50_3637        NfsA         ec50      3637 -0.0055669317
## 349       NfsA_ec50_3637        NfsA         ec50      3637  0.3247082162
## 350       NfsA_ec50_3637        NfsA         ec50      3637 -0.1909947989
## 351       NfsA_ec50_3637        NfsA         ec50      3637  0.2095135629
## 352       NfsA_ec50_3637        NfsA         ec50      3637 -0.4965798123
## 353       NfsA_ec50_3637        NfsA         ec50      3637 -0.1818802618
## 354       NfsA_ec50_3637        NfsA         ec50      3637 -0.0123674545
## 355       NfsA_ec50_3637        NfsA         ec50      3637 -0.0199667765
## 356       NfsA_ec50_3637        NfsA         ec50      3637  0.1093012756
## 357       NfsA_ec50_3637        NfsA         ec50      3637 -0.1985136418
## 358       NfsA_ec50_3637        NfsA         ec50      3637 -0.4374371314
## 359       NfsA_ec50_3637        NfsA         ec50      3637  0.0334701705
## 360       NfsA_ec50_3637        NfsA         ec50      3637  0.1032024493
## 361       NfsA_ec50_3637        NfsA         ec50      3637 -0.1092382943
## 362       NfsA_ec50_3637        NfsA         ec50      3637 -0.0813533852
## 363       NfsA_ec50_3637        NfsA         ec50      3637 -0.1803026806
## 364       NfsA_ec50_3637        NfsA         ec50      3637 -0.0089813811
## 365       NfsA_ec50_3637        NfsA         ec50      3637 -0.0887530639
## 366       NfsA_ec50_3637        NfsA         ec50      3637  0.2248910047
## 367       NfsA_ec50_3637        NfsA         ec50      3637  0.0124182728
## 368       NfsA_ec50_3637        NfsA         ec50      3637 -0.1179390815
## 369       NfsA_ec50_3637        NfsA         ec50      3637  0.2463504336
## 370       NfsA_ec50_3637        NfsA         ec50      3637 -0.0788818339
## 371       NfsA_ec50_3637        NfsA         ec50      3637 -0.0385841910
## 372       NfsA_ec50_3637        NfsA         ec50      3637  0.0355885181
## 373       NfsA_ec50_3637        NfsA         ec50      3637 -0.2867550554
## 374       NfsA_ec50_3637        NfsA         ec50      3637 -0.0555546182
## 375       NfsA_ec50_3637        NfsA         ec50      3637 -0.0906614568
## 376       NfsA_ec50_3637        NfsA         ec50      3637  0.0375301472
## 377       NfsA_ec50_3637        NfsA         ec50      3637  0.0669668060
## 378       NfsA_ec50_3637        NfsA         ec50      3637  0.1206408259
## 379       NfsA_ec50_3637        NfsA         ec50      3637 -0.3608554723
## 380       NfsA_ec50_3637        NfsA         ec50      3637 -0.0562624733
## 381 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.3320456373
## 382 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.0018436095
## 383 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.3308587296
## 384 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.0257601887
## 385 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.0309832222
## 386 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.1279913659
## 387 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.0362998491
## 388 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.0051600705
## 389 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.2345885840
## 390 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.0021184273
## 391 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.4520073760
## 392 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.5072447682
## 393 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2322662635
## 394 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2011161233
## 395 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.3675270797
## 396 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0776672023
## 397 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1469379670
## 398 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1729186185
## 399 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1034867917
## 400 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0245774437
## 401 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0962601272
## 402 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0374030371
## 403 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.3571733510
## 404 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1761771660
## 405 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2310929181
## 406 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1550315534
## 407 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0836030575
## 408 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2079829987
## 409 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0636474609
## 410 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1537873915
## 411 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.3862382251
## 412 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1370188947
## 413 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1334705379
## 414 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0620513175
## 415 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0826698657
## 416 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0804127445
## 417 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1021430941
## 418 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0291861163
## 419 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1708379190
## 420 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1726222318
## 421 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0526166129
## 422 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0839710533
## 423 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0835174321
## 424 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0177659322
## 425 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0023086958
## 426 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1701052593
## 427 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2339087945
## 428 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1575969765
## 429 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1286436265
## 430 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2046346501
## 431 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1116113314
## 432 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.3103155767
## 433 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1005210644
## 434 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1105589638
## 435 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2858996573
## 436 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.2687554330
## 437 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0179728892
## 438 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1203778663
## 439 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2929293612
## 440 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1523968960
## 441 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1963371276
## 442 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1482655882
## 443 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1611956215
## 444 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.1346938665
## 445 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.2240176489
## 446 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.0151834977
## 447 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.0503255758
## 448 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.1977983004
## 449 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0610598579
## 450 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0409902741
## 451 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0960047615
## 452 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0319766797
## 453 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.2597174797
## 454 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1646899644
## 455 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0126269844
## 456 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0418167864
## 457 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1029315531
## 458 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0897087574
## 459 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0399018082
## 460 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0179960429
## 461 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0975201602
## 462 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0398744580
## 463 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0192487103
## 464 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0011875442
## 465 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0520545989
## 466 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1274031534
## 467 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0016661053
## 468 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0788291217
## 469 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1658703587
## 470 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0128113183
## 471 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0273208218
## 472 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0032190631
## 473 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0337077327
## 474 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0415368472
## 475 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1253463593
## 476 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0134890705
## 477 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0119185296
## 478 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0273295870
## 479 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.3584109834
## 480 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0458425116
## 481 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1030318338
## 482 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0849993482
## 483 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.2143528103
## 484 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.4726135136
## 485 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.2156369908
## 486 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1649320251
## 487 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1671852596
## 488 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0842277227
## 489 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0864575198
## 490 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0255847522
## 491 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0684301233
## 492 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.2718614986
## 493 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0723157477
## 494 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0957845105
## 495 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1378797455
## 496 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.1277320188
## 497 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.3382977306
## 498 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0046617010
## 499 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0642127088
## 500 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1439535601
## 501 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0021469899
## 502 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0106092530
## 503 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0314345394
## 504 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.1211614184
## 505 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0413610788
## 506 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.0566767551
## 507 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.0922228366
## 508       PTE_catact_2NH         PTE       catact       2NH  0.7285390388
## 509       PTE_catact_2NH         PTE       catact       2NH  0.6373364226
## 510       PTE_catact_2NH         PTE       catact       2NH -0.2450705571
## 511       PTE_catact_2NH         PTE       catact       2NH -0.4956750948
## 512       PTE_catact_2NH         PTE       catact       2NH -0.6668673267
## 513       PTE_catact_2NH         PTE       catact       2NH  0.2725240242
## 514       PTE_catact_2NH         PTE       catact       2NH -0.5812863605
## 515       PTE_catact_2NH         PTE       catact       2NH -1.6213040114
## 516       PTE_catact_2NH         PTE       catact       2NH -0.2268754483
## 517       PTE_catact_2NH         PTE       catact       2NH -0.0235867814
## 518       PTE_catact_2NH         PTE       catact       2NH -0.2614621340
## 519       PTE_catact_2NH         PTE       catact       2NH  0.6199565695
## 520       PTE_catact_2NH         PTE       catact       2NH  0.3578151577
## 521       PTE_catact_2NH         PTE       catact       2NH  0.0947106215
## 522       PTE_catact_2NH         PTE       catact       2NH -0.0564936082
## 523       PTE_catact_2NH         PTE       catact       2NH  0.0769863183
## 524       PTE_catact_2NH         PTE       catact       2NH  0.0904603121
## 525       PTE_catact_2NH         PTE       catact       2NH  0.2717675785
## 526       PTE_catact_2NH         PTE       catact       2NH  0.8347845561
## 527       PTE_catact_2NH         PTE       catact       2NH  0.3473048566
## 528       PTE_catact_2NH         PTE       catact       2NH -0.1365751694
## 529       PTE_catact_2NH         PTE       catact       2NH -0.5099230009
## 530       PTE_catact_2NH         PTE       catact       2NH  0.2087296979
## 531       PTE_catact_2NH         PTE       catact       2NH -0.4068882602
## 532       PTE_catact_2NH         PTE       catact       2NH -0.2946447369
## 533       PTE_catact_2NH         PTE       catact       2NH -0.2780698745
## 534       PTE_catact_2NH         PTE       catact       2NH -0.1593031117
## 535       PTE_catact_2NH         PTE       catact       2NH -0.5955769994
## 536       PTE_catact_2NH         PTE       catact       2NH -0.0596301158
## 537       PTE_catact_2NH         PTE       catact       2NH -0.1570006989
## 538       PTE_catact_2NH         PTE       catact       2NH  1.4715059467
## 539       PTE_catact_2NH         PTE       catact       2NH  0.0137585293
## 540       PTE_catact_2NH         PTE       catact       2NH -0.1103822900
## 541       PTE_catact_2NH         PTE       catact       2NH -0.3977623654
## 542       PTE_catact_2NH         PTE       catact       2NH -0.2347492538
## 543       PTE_catact_2NH         PTE       catact       2NH -0.2301507057
## 544       PTE_catact_2NH         PTE       catact       2NH -0.3752671809
## 545       PTE_catact_2NH         PTE       catact       2NH -1.1402236356
## 546       PTE_catact_2NH         PTE       catact       2NH -0.2300782640
## 547       PTE_catact_2NH         PTE       catact       2NH  0.3597276308
## 548       PTE_catact_2NH         PTE       catact       2NH  0.1752027516
## 549       PTE_catact_2NH         PTE       catact       2NH  0.0086221024
## 550       PTE_catact_2NH         PTE       catact       2NH  0.0744053780
## 551       PTE_catact_2NH         PTE       catact       2NH -0.0655980266
## 552       PTE_catact_2NH         PTE       catact       2NH  0.1022297216
## 553       PTE_catact_2NH         PTE       catact       2NH  0.1688986986
## 554       PTE_catact_2NH         PTE       catact       2NH  0.0224243247
## 555       PTE_catact_2NH         PTE       catact       2NH  0.0256556361
## 556       PTE_catact_2NH         PTE       catact       2NH -0.0935406092
## 557       PTE_catact_2NH         PTE       catact       2NH -0.2015806584
## 558       PTE_catact_2NH         PTE       catact       2NH  0.3272962613
## 559       PTE_catact_2NH         PTE       catact       2NH  0.4764903090
## 560       PTE_catact_2NH         PTE       catact       2NH  0.4376029757
## 561       PTE_catact_2NH         PTE       catact       2NH  0.2179017588
## 562       PTE_catact_2NH         PTE       catact       2NH -0.1814104041
## 563       PTE_catact_2NH         PTE       catact       2NH -0.0949573899
## 564       PTE_catact_2NH         PTE       catact       2NH  0.0065038763
## 565       PTE_catact_2NH         PTE       catact       2NH -0.1228109891
## 566       PTE_catact_2NH         PTE       catact       2NH -0.0440976935
## 567    TEM_MIC_weinreich         TEM          MIC weinreich  0.9959252876
## 568    TEM_MIC_weinreich         TEM          MIC weinreich -0.6380093140
## 569    TEM_MIC_weinreich         TEM          MIC weinreich -0.5617283740
## 570    TEM_MIC_weinreich         TEM          MIC weinreich  0.4404367458
## 571    TEM_MIC_weinreich         TEM          MIC weinreich  0.6828096293
## 572    TEM_MIC_weinreich         TEM          MIC weinreich  0.7668805522
## 573    TEM_MIC_weinreich         TEM          MIC weinreich  0.0416191642
## 574    TEM_MIC_weinreich         TEM          MIC weinreich  0.1349017256
## 575    TEM_MIC_weinreich         TEM          MIC weinreich -0.2531919803
## 576    TEM_MIC_weinreich         TEM          MIC weinreich -0.9029548338
## 577    TEM_MIC_weinreich         TEM          MIC weinreich  0.2946085787
## 578    TEM_MIC_weinreich         TEM          MIC weinreich  0.1589193176
## 579    TEM_MIC_weinreich         TEM          MIC weinreich  0.0340169486
## 580    TEM_MIC_weinreich         TEM          MIC weinreich  0.5607717676
## 581    TEM_MIC_weinreich         TEM          MIC weinreich  0.0323045028
## 582    TEM_MIC_weinreich         TEM          MIC weinreich -0.7790332707
## 583    TEM_MIC_weinreich         TEM          MIC weinreich -0.0333338299
## 584    TEM_MIC_weinreich         TEM          MIC weinreich  0.4991308025
## 585    TEM_MIC_weinreich         TEM          MIC weinreich  0.4495140405
## 586    TEM_MIC_weinreich         TEM          MIC weinreich -0.2029847382
## 587    TEM_MIC_weinreich         TEM          MIC weinreich  0.1679882204
## 588    TEM_MIC_weinreich         TEM          MIC weinreich  1.5870060093
## 589    TEM_MIC_weinreich         TEM          MIC weinreich -1.1900805252
## 590    TEM_MIC_weinreich         TEM          MIC weinreich -0.9755374929
## 591    TEM_MIC_weinreich         TEM          MIC weinreich -0.8185917634
## 592    TEM_MIC_weinreich         TEM          MIC weinreich  0.1233783106
##     traj_effects access access_no_idio access_mean access_w_mean access_w_idio
## 1    0.643452676     NA             NA          NA            NA            NA
## 2    1.383815366      2              2           2             0             0
## 3    1.910624405      3              1           1            -2             2
## 4    2.324282455      3              4           4             1            -1
## 5    2.103803721      0              0           0             0             0
## 6    2.158362492      2              6           2             0            -4
## 7    2.294466226      3              0           1            -2             3
## 8    2.222716471      4              4           1            -3             0
## 9    2.313867220      5              0           0            -5             5
## 10   2.227886705      4              4           4             0             0
## 11   2.071882007      3              1           1            -2             2
## 12   2.184691431      3              1           2            -1             2
## 13   2.278753601      4              2           2            -2             2
## 14  -3.031517051      0              3           1             1            -3
## 15   1.856124444      3              3           3             0             0
## 16   1.710963119      1              1           4             3             0
## 17   1.983175072      3              1           0            -3             2
## 18   1.146128036      2              2           2             0             0
## 19   2.322219295      3              0           0            -3             3
## 20   2.324282455      4              1           0            -4             3
## 21   2.326335861      3              4           4             1            -1
## 22   2.086359831      3              3           0            -3             0
## 23   2.217483944      4              1           1            -3             3
## 24   2.049218023      3              2           2            -1             1
## 25   1.933993164      2              2           2             0             0
## 26   2.320146286      3              3           3             0             0
## 27   2.311753861      3              1           4             1             2
## 28   2.283301229      3              0           3             0             3
## 29   1.713490543      2              2           2             0             0
## 30   2.082785370      3              3           3             0             0
## 31   1.557507202      2              2           2             0             0
## 32   0.728353782     NA             NA          NA            NA            NA
## 33  -3.031517051      0              2           2             2            -2
## 34   0.717670503      1              1           1             0             0
## 35   2.324282455      4              4           2            -2             0
## 36  -0.798602876      1              1           0            -1             0
## 37  -0.422508200      0              4           4             4            -4
## 38   1.187520721      3              1           1            -2             2
## 39   1.973589623      4              4           4             0             0
## 40   1.363611980      3              0           1            -2             3
## 41   1.187520721      1              2           1             0            -1
## 42  -0.804100348      0              1           2             2            -1
## 43  -3.031517051      0              0           0             0             0
## 44  -0.277366077      0              0           0             0             0
## 45   0.706717782      1              2           2             1            -1
## 46  -0.543633967      0              2           2             2            -2
## 47   0.822821645      1              2           2             1            -1
## 48   0.307496038     NA             NA          NA            NA            NA
## 49   2.079181246      2              3           1            -1            -1
## 50  -0.228412519      0              0           0             0             0
## 51   2.049218023      2              1           1            -1             1
## 52   1.025305865      2              2           2             0             0
## 53   1.557507202      2              3           0            -2            -1
## 54   1.049218023      1              2           2             1            -1
## 55   1.824125834      1              2           1             0            -1
## 56  -0.157390760      0              2           3             3            -2
## 57   1.692846919      1              2           1             0            -1
## 58   0.267171728     NA             NA          NA            NA            NA
## 59   1.964730921      2              2           1            -1             0
## 60   1.472756449     NA             NA          NA            NA            NA
## 61   0.352182518     NA             NA          NA            NA            NA
## 62   1.025305865      2              2           2             0             0
## 63   3.082785370      3              3           3             0             0
## 64   4.389166084      4              4           4             0             0
## 65   4.281033367      4              4           4             0             0
## 66   2.606381365      3              3           3             0             0
## 67   4.658964843      4              4           4             0             0
## 68   2.799340549      3              3           3             0             0
## 69   1.700703717      2              2           2             0             0
## 70   2.870988814      3              3           3             0             0
## 71   4.198657087      4              0           4             0             4
## 72   2.774516966      3              3           3             0             0
## 73   1.484299839      2              2           2             0             0
## 74   3.049218023      3              3           3             0             0
## 75   1.804139432      2              2           2             0             0
## 76   0.342422681     NA             NA          NA            NA            NA
## 77   1.828015064      2              2           2             0             0
## 78   3.017033339      3              3           3             0             0
## 79   1.324282455      2              2           2             0             0
## 80   3.675778342      3              3           3             0             0
## 81   1.283301229      2              2           2             0             0
## 82   1.828015064      2              2           2             0             0
## 83   3.096910013      3              3           3             0             0
## 84   0.346352974     NA             NA          NA            NA            NA
## 85   2.738780558      2              2           2             0             0
## 86   0.620136055     NA             NA          NA            NA            NA
## 87   0.352182518     NA             NA          NA            NA            NA
## 88   1.025305865      2              2           2             0             0
## 89   3.082785370      3              3           3             0             0
## 90   3.962369336      4              4           4             0             0
## 91   2.037426498      3              3           3             0             0
## 92   4.117271296      4              4           4             0             0
## 93   2.799340549      3              3           3             0             0
## 94   1.700703717      2              2           2             0             0
## 95   2.981365509      3              3           3             0             0
## 96   4.110589710      4              2           4             0             2
## 97   2.774516966      3              3           3             0             0
## 98   1.643452676      2              2           2             0             0
## 99   2.450249108      3              3           3             0             0
## 100  1.804139432      2              2           2             0             0
## 101  0.342422681     NA             NA          NA            NA            NA
## 102  1.828015064      2              2           2             0             0
## 103  2.820857989      3              3           3             0             0
## 104  3.986771734      4              4           4             0             0
## 105  1.252853031      2              2           2             0             0
## 106  2.840733235      3              3           3             0             0
## 107  1.283301229      2              2           2             0             0
## 108  2.301029996      2              2           2             0             0
## 109  3.056904851      3              3           3             0             0
## 110  0.359835482     NA             NA          NA            NA            NA
## 111  1.075546961      2              2           2             0             0
## 112  0.620136055     NA             NA          NA            NA            NA
## 113  0.271841607     NA             NA          NA            NA            NA
## 114  0.755112266      2              2           2             0             0
## 115  1.107209970      3              1           2            -1             2
## 116 -0.395773947      1              1           1             0             0
## 117 -0.094743951      2              2           2             0             0
## 118  0.980457892      2              2           2             0             0
## 119  0.551449998      1              1           1             0             0
## 120  0.857935265      2              1           3             1             1
## 121  0.987666265      1              2           2             1            -1
## 122 -0.787812396     NA             NA          NA            NA            NA
## 123 -0.153044675      1              1           1             0             0
## 124  0.668385917     NA             NA          NA            NA            NA
## 125  0.930949031     NA             NA          NA            NA            NA
## 126  1.158362492      2              2           2             0             0
## 127  1.206825876      3              3           3             0             0
## 128  0.544068044      2              2           2             0             0
## 129  0.176091259      2              2           2             0             0
## 130  2.079181246      3              3           3             0             0
## 131  2.204119983      3              1           3             0             2
## 132  1.100370545      2              2           2             0             0
## 133  0.110589710      1              1           1             0             0
## 134  1.392696953      4              4           4             0             0
## 135  0.708420900      0              0           1             1             0
## 136 -0.331614083      1              1           1             0             0
## 137  0.348304863      2              0           2             0             2
## 138  0.710963119      1              2           2             1            -1
## 139 -0.031984286     NA             NA          NA            NA            NA
## 140 -0.144480844      0              0           2             2             0
## 141 -0.204119983      0              0           0             0             0
## 142 -0.173277480      2              3           3             1            -1
## 143 -0.455931956      1              1           1             0             0
## 144  0.071882007      3              4           3             0            -1
## 145 -0.155522824      2              1           2             0             1
## 146 -0.118045029      2              3           3             1            -1
## 147  0.326335861      3              3           3             0             0
## 148 -0.196542884      1              1           2             1             0
## 149 -0.131355562      2              0           0            -2             2
## 150 -0.402304814      1              3           3             2            -2
## 151  0.260071388      3              1           3             0             2
## 152 -0.071604148      3              4           4             1            -1
## 153 -0.081445469      2              0           1            -1             2
## 154  0.459392488      3              3           3             0             0
## 155 -0.177178355      0              0           0             0             0
## 156 -0.077274542      0              0           0             0             0
## 157 -0.343901798      0              0           0             0             0
## 158 -0.661543506      0              2           2             2            -2
## 159 -0.368556231      1              1           1             0             0
## 160 -0.080398976      2              3           3             1            -1
## 161 -0.534617149      0              0           0             0             0
## 162 -0.151810883      1              3           3             2            -2
## 163 -0.090443971      0              0           0             0             0
## 164 -0.241845378      0              0           0             0             0
## 165 -0.542118103      0              0           0             0             0
## 166 -0.232844134      1              3           3             2            -2
## 167 -0.073657553      1              1           0            -1             0
## 168 -0.501689446      0              1           1             1            -1
## 169  0.037426498      2              1           1            -1             1
## 170 -0.059981845      0              0           2             2             0
## 171 -0.012333735     NA             NA          NA            NA            NA
## 172 -0.053056729      0              0           0             0             0
## 173  0.004321374      3              0           0            -3             3
## 174  0.235528447      2              4           4             2            -2
## 175  0.537819095      4              2           2            -2             2
## 176  0.017033339      3              4           4             1            -1
## 177  0.423245874      2              2           2             0             0
## 178  0.688419822      4              4           4             0             0
## 179 -0.095284455      0              0           0             0             0
## 180 -0.026872146      0              0           2             2             0
## 181  0.296665190      2              2           1            -1             0
## 182  0.523746467      3              4           4             1            -1
## 183  0.033423755      3              1           1            -2             2
## 184  0.457881897      2              1           2             0             1
## 185  0.542825427      2              3           3             1            -1
## 186 -0.093126465      0              0           0             0             0
## 187 -0.010995384     NA             NA          NA            NA            NA
## 188 -0.085656843      0              0           0             0             0
## 189  0.158362492      1              1           1             0             0
## 190  0.434568904      2              4           4             2            -2
## 191 -0.006123085      3              0           0            -3             3
## 192  0.334453751      1              1           1             0             0
## 193  0.610660163      3              2           2            -1             1
## 194 -0.069050969      0              0           1             1             0
## 195 -0.008773924     NA             NA          NA            NA            NA
## 196  0.212187604      1              1           1             0             0
## 197  0.488550717      2              2           2             0             0
## 198 -0.034798299      1              0           1             0             1
## 199  0.582063363      2              1           2             0             1
## 200 -0.054039296     NA             NA          NA            NA            NA
## 201  0.056904851     NA             NA          NA            NA            NA
## 202  0.075546961      2              1           2             0             1
## 203 -0.083546051      1              1           0            -1             0
## 204 -0.024108864      2              2           2             0             0
## 205 -0.077274542      1              4           4             3            -3
## 206  0.734799830      4              6           6             2            -2
## 207  0.979092901      7              4           7             0             3
## 208 -0.144480844      2              0           4             2             2
## 209  0.737987326      4              4           4             0             0
## 210  0.975891136      5              5           6             1             0
## 211 -0.171340103      2              2           4             2             0
## 212  0.004321374      3              4           4             1            -1
## 213  0.758911892      4              2           3            -1             2
## 214  0.915927212      5              6           6             1            -1
## 215 -0.089375595      1              1           1             0             0
## 216  0.804139432      4              4           4             0             0
## 217 -0.208309351      0              0           0             0             0
## 218  0.075546961      3              1           2            -1             2
## 219 -0.053547735      3              3           3             0             0
## 220  0.434568904      4              2           2            -2             2
## 221  0.598790507      3              6           5             2            -3
## 222  0.004321374      5              5           3            -2             0
## 223  0.374748346      2              3           4             2            -1
## 224  0.752048448      4              3           3            -1             1
## 225  0.004321374      3              3           4             1             0
## 226 -0.071604148      2              0           0            -2             2
## 227  0.396199347      2              4           4             2            -2
## 228  0.668385917      4              2           2            -2             2
## 229 -0.022733788      4              4           4             0             0
## 230  0.413299764      2              1           2             0             1
## 231  0.762678564      4              4           4             0             0
## 232 -0.029653124      2              2           0            -2             0
## 233  0.060697840      2              1           1            -1             1
## 234  0.033423755      2              1           0            -2             1
## 235  0.068185862      4              4           4             0             0
## 236  0.661812686      4              2           3            -1             2
## 237  0.874481818      6              6           6             0             0
## 238 -0.024108864      2              1           4             2             1
## 239  0.691081492      3              4           4             1            -1
## 240  0.831869774      4              4           4             0             0
## 241 -0.083546051      1              3           3             2            -2
## 242  0.041392685      2              0           1            -1             2
## 243  0.647382970      3              4           4             1            -1
## 244  0.867467488      5              4           2            -3             1
## 245  0.029383778      2              4           4             2            -2
## 246  0.736396502      3              3           3             0             0
## 247 -0.076238039      1              1           0            -1             0
## 248 -0.016373713      0              1           2             2            -1
## 249 -0.181114585      0              0           0             0             0
## 250  0.530199698      2              4           4             2            -2
## 251  0.654176542      4              2           2            -2             2
## 252 -0.067019178      2              3           3             1            -1
## 253  0.564666064      2              2           2             0             0
## 254  0.712649702      3              4           4             1            -1
## 255 -0.034798299      2              0           0            -2             2
## 256 -0.151810883      0              1           2             2            -1
## 257  0.562292864      2              1           2             0             1
## 258  0.632457292      3              4           4             1            -1
## 259 -0.166215625      0              0           0             0             0
## 260 -0.040481623      1              1           0            -1             0
## 261 -0.071604148     NA             NA          NA            NA            NA
## 262 -0.013676223      1              0           1             0             1
## 263 -0.077274542      0              2           3             3            -2
## 264 -0.077274542      3              0           0            -3             3
## 265  0.459392488      4              3           4             0             1
## 266  0.636487896      4              4           6             2             0
## 267 -0.019088062      3              5           3             0            -2
## 268 -0.065501549      2              1           1            -1             1
## 269  0.521138084      3              5           2            -1            -2
## 270  0.113943352      2              0           1            -1             2
## 271 -0.155522824      1              3           3             2            -2
## 272  0.453318340      3              3           3             0             0
## 273  0.732393760      5              5           5             0             0
## 274 -0.107905397      2              0           0            -2             2
## 275  0.029383778      2              1           1            -1             1
## 276  0.526339277      4              2           2            -2             2
## 277 -0.010995384      1              3           3             2            -2
## 278 -0.074172425      0              1           0             0            -1
## 279 -0.166215625      1              2           2             1            -1
## 280 -0.208309351      1              1           0            -1             0
## 281  0.409933123      2              5           5             3            -3
## 282 -0.071604148      2              0           0            -2             2
## 283 -0.372634143      0              0           0             0             0
## 284  0.423245874      2              2           2             0             0
## 285  0.167317335      2              3           3             1            -1
## 286 -0.250263684      1              0           0            -1             1
## 287 -0.111259039      2              2           2             0             0
## 288  0.557507202      4              2           2            -2             2
## 289 -0.196542884      2              2           2             0             0
## 290 -0.327902142      0              1           1             1            -1
## 291  0.481442629      2              1           2             0             1
## 292  0.143014800      2              0           2             0             2
## 293 -0.012333735     NA             NA          NA            NA            NA
## 294  0.113943352      2              1           1            -1             1
## 295  0.103803721      2              3           3             1            -1
## 296  0.636487896      3              4           3             0            -1
## 297  0.868644438      5              5           2            -3             0
## 298  0.064457989      2              2           2             0             0
## 299  0.488550717      3              3           3             0             0
## 300  0.667452953      4              1           2            -2             3
## 301  0.245512668      3              3           3             0             0
## 302 -0.101823517      1              0           1             0             1
## 303  0.708420900      3              3           3             0             0
## 304  0.507855872      3              2           3             0             1
## 305 -0.065501549      2              2           2             0             0
## 306  0.463892989      1              1           2             1             0
## 307  0.503790683      2              3           2             0            -1
## 308  0.004321374      2              0           0            -2             2
## 309  0.021189299     NA             NA          NA            NA            NA
## 310 -0.141462802      1              1           0            -1             0
## 311  0.537819095      3              3           3             0             0
## 312  0.665580991      4              1           2            -2             3
## 313 -0.065501549      2              2           2             0             0
## 314  0.477121255      1              2           1             0            -1
## 315  0.654176542      3              3           3             0             0
## 316  0.209515015      2              1           1            -1             1
## 317 -0.301899454     NA             NA          NA            NA            NA
## 318  0.505149978      2              1           2             0             1
## 319  0.367355921      1              3           3             2            -2
## 320 -0.292429824      1              0           0            -1             1
## 321  0.599883072      2              1           1            -1             1
## 322 -0.078313525     NA             NA          NA            NA            NA
## 323  0.056904851     NA             NA          NA            NA            NA
## 324  0.086359831      2              1           2             0             1
## 325  0.008600172      1              3           2             1            -2
## 326  0.029383778      2              1           2             0             1
## 327 -0.166215625      2              2           0            -2             0
## 328  0.979548375      5              6           6             1            -1
## 329  0.155336037      5              6           6             1            -1
## 330  0.935003151      5              3           2            -3             2
## 331  0.929929560      5              6           6             1            -1
## 332  0.723455672      5              0           2            -3             5
## 333 -0.173277480      0              0           0             0             0
## 334  0.941511433      5              5           2            -3             0
## 335  0.103803721      4              0           0            -4             4
## 336  0.696356389      3              4           3             0            -1
## 337  0.836324116      4              1           1            -3             3
## 338  0.372912003      4              4           4             0             0
## 339  0.225309282      3              3           3             0             0
## 340 -0.101823517      3              1           1            -2             2
## 341  0.727541257      4              5           2            -2            -1
## 342  0.816903839      5              6           6             1            -1
## 343 -0.018634491      3              0           0            -3             3
## 344  0.627365857      3              3           4             1             0
## 345  0.851869601      5              0           2            -3             5
## 346  0.397940009      4              4           4             0             0
## 347 -0.118045029      2              2           2             0             0
## 348  0.705863712      3              4           4             1            -1
## 349  0.803457116      4              1           3            -1             3
## 350 -0.095284455      2              4           4             2            -2
## 351  0.582063363      2              1           2             0             1
## 352  0.824776462      4              4           4             0             0
## 353  0.313867220      3              1           1            -2             2
## 354  0.060697840      2              1           1            -1             1
## 355  0.146128036      2              3           3             1            -1
## 356 -0.224753740      1              0           1             0             1
## 357  1.000000000      5              1           1            -4             4
## 358  0.912753304      4              6           6             2            -2
## 359  0.107209970      4              0           0            -4             4
## 360  0.795880017      3              3           4             1             0
## 361  0.883093359      4              0           0            -4             4
## 362  0.359835482      4              4           4             0             0
## 363 -0.144480844      1              2           1             0            -1
## 364  0.649334859      1              4           4             3            -3
## 365  0.021189299      3              4           4             1            -1
## 366  0.278753601      3              1           1            -2             2
## 367  0.178976947      2              2           2             0             0
## 368 -0.287350298      0              2           2             2            -2
## 369  0.786751422      4              1           2            -2             3
## 370  0.800717078      5              1           1            -4             4
## 371  0.012837225      3              4           3             0            -1
## 372  0.745074792      3              3           3             0             0
## 373  0.602059991      1              4           4             3            -3
## 374  0.348304863      3              1           1            -2             2
## 375 -0.192464972      1              1           0            -1             0
## 376  0.720159303      3              3           3             0             0
## 377  0.758154622      4              4           4             0             0
## 378 -0.016373713      3              0           0            -3             3
## 379  0.742725131      3              1           1            -2             2
## 380 -0.449771647      0              1           1             1            -1
## 381  0.075546961     NA             NA          NA            NA            NA
## 382  0.264817823      2              1           1            -1             1
## 383 -0.019996628     NA             NA          NA            NA            NA
## 384  0.113943352     NA             NA          NA            NA            NA
## 385  0.045322979      0              2           2             2            -2
## 386  0.193124598      2              2           3             1             0
## 387  0.060697840      1              1           1             0             0
## 388  0.424881637      2              2           2             0             0
## 389  1.064457989      3              2           3             0             1
## 390  1.041392685      2              3           3             1            -1
## 391  1.041392685      2              2           2             0             0
## 392  0.383815366     NA             NA          NA            NA            NA
## 393  0.416640507      2              1           2             0             1
## 394  0.938019097      3              3           2            -1             0
## 395  1.365487985      4              4           4             0             0
## 396  1.146128036      3              2           3             0             1
## 397  0.773054693      2              2           2             0             0
## 398 -0.012333735     NA             NA          NA            NA            NA
## 399  0.513217600      2              1           2             0             1
## 400  1.041392685      3              3           3             0             0
## 401  0.068185862      1              1           2             1             0
## 402  0.770852012      2              2           2             0             0
## 403  0.139879086     NA             NA          NA            NA            NA
## 404  0.008600172     NA             NA          NA            NA            NA
## 405  0.195899652      1              2           1             0            -1
## 406  0.462397998      3              2           2            -1             1
## 407  0.691965103      3              3           3             0             0
## 408  1.012837225      4              4           4             0             0
## 409  0.755874856      3              3           3             0             0
## 410  0.332438460      2              2           2             0             0
## 411  0.238046103      2              0           1            -1             2
## 412  0.100370545      0              2           2             2            -2
## 413  0.017033339      2              1           2             0             1
## 414  0.374748346      2              2           2             0             0
## 415  0.764922985      3              3           3             0             0
## 416  0.146128036      2              2           3             1             0
## 417  0.149219113      1              2           1             0            -1
## 418  0.217483944      2              2           2             0             0
## 419  0.158362492      2              2           0            -2             0
## 420  0.086359831      2              1           2             0             1
## 421  0.472756449      2              2           2             0             0
## 422  0.758154622      3              3           3             0             0
## 423  0.997823081      4              5           5             1            -1
## 424  1.260071388      4              4           4             0             0
## 425  0.713490543      3              2           2            -1             1
## 426  1.322219295      4              5           4             0            -1
## 427  0.915399835      3              3           3             0             0
## 428  0.008600172      1              3           0            -1            -2
## 429  0.589949601      4              3           2            -2             1
## 430  0.898725182      4              5           5             1            -1
## 431  0.274157849      2              2           1            -1             0
## 432  0.570542940      3              2           3             0             1
## 433  0.840106094      3              2           3             0             1
## 434  0.365487985      2              3           3             1            -1
## 435 -0.008773924     NA             NA          NA            NA            NA
## 436  0.683947131      2              1           2             0             1
## 437  0.820201459      3              3           3             0             0
## 438  1.113943352      4              3           4             0             1
## 439  1.568201724      4              4           4             0             0
## 440  0.841984805      3              3           3             0             0
## 441  1.361727836      3              3           3             0             0
## 442 -0.014573526      0              0           0             0             0
## 443  0.478566496      1              3           1             0            -2
## 444  0.980003372      3              3           2            -1             0
## 445  0.281033367      2              2           2             0             0
## 446  0.539076099      2              1           2             0             1
## 447  0.898176483      3              3           3             0             0
## 448  0.380211242      2              1           2             0             1
## 449  0.004321374     NA             NA          NA            NA            NA
## 450  0.152288344      2              2           1            -1             0
## 451  0.621176282      3              3           3             0             0
## 452  0.611723308      2              4           4             2            -2
## 453  0.501059262      4              0           1            -3             4
## 454  0.376576957      2              3           4             2            -1
## 455  0.089905111      2              3           3             1            -1
## 456  0.243038049      3              4           4             1            -1
## 457  0.278753601      3              3           3             0             0
## 458  0.557507202      2              2           2             0             0
## 459  0.557507202      3              2           2            -1             1
## 460  0.460897843      2              4           4             2            -2
## 461  0.369215857      2              2           1            -1             0
## 462  0.004321374      1              2           0            -1            -1
## 463  0.110589710      3              0           0            -3             3
## 464 -0.031517051      0              2           2             2            -2
## 465  0.045322979     NA             NA          NA            NA            NA
## 466  0.506505032      2              2           1            -1             0
## 467  0.654176542      3              2           2            -1             1
## 468  0.442479769      1              4           4             3            -3
## 469  0.466867620      2              2           1            -1             0
## 470  0.086359831      2              2           2             0             0
## 471  0.170261715      3              3           2            -1             0
## 472  0.155336037      2              2           2             0             0
## 473  0.403120521      1              2           2             1            -1
## 474  0.481442629      3              1           1            -2             2
## 475  0.352182518      1              2           1             0            -1
## 476  0.025305865     NA             NA          NA            NA            NA
## 477  0.033423755      1              2           2             1            -1
## 478  0.041392685     NA             NA          NA            NA            NA
## 479  0.056904851     NA             NA          NA            NA            NA
## 480  0.064457989      2              2           2             0             0
## 481 -0.008773924      0              3           2             2            -3
## 482  1.170261715      3              3           3             0             0
## 483  1.130333768      3              3           2            -1             0
## 484  1.212187604      4              6           4             0            -2
## 485  1.232996110      4              2           3            -1             2
## 486  0.117271296      3              0           2            -1             3
## 487  0.212187604      2              2           0            -2             0
## 488  0.269512944      3              4           4             1            -1
## 489  1.332438460      3              4           4             1            -1
## 490  1.276461804      3              2           2            -1             1
## 491 -0.006563770      0              0           0             0             0
## 492  0.053078443      1              4           2             1            -3
## 493  0.201397124      3              1           2            -1             2
## 494  0.133538908      2              2           0            -2             0
## 495  1.123851641      3              3           2            -1             0
## 496  1.093421685      3              4           4             1            -1
## 497  1.110589710      4              2           2            -2             2
## 498  0.967079734      2              4           4             2            -2
## 499  0.127104798      2              2           3             1             0
## 500  0.243038049      4              4           4             0             0
## 501  0.235528447      3              3           3             0             0
## 502  1.071882007      3              2           2            -1             1
## 503  1.217483944      4              4           4             0             0
## 504  1.149219113      3              2           2            -1             1
## 505  0.012837225      0              2           1             1            -2
## 506  0.075546961      3              0           0            -3             3
## 507  0.053078443      1              2           2             1            -1
## 508  0.613841822     NA             NA          NA            NA            NA
## 509  2.717670503      2              2           2             0             0
## 510  2.401400541      2              3           2             0            -1
## 511  2.799340549      3              3           2            -1             0
## 512  3.198657087      4              5           5             1            -1
## 513  2.999130541      1              1           1             0             0
## 514  3.107209970      5              5           5             0             0
## 515  3.100370545      4              5           4             0            -1
## 516  2.831229694      4              2           2            -2             2
## 517  2.912222057      3              3           3             0             0
## 518  3.117271296      4              4           4             0             0
## 519  3.000000000      4              1           5             1             3
## 520  2.685741739      3              3           3             0             0
## 521  2.812244697      3              2           3             0             1
## 522  2.187520721      2              3           3             1            -1
## 523  0.572871602      1              1           1             0             0
## 524  0.570542940      1              3           3             2            -2
## 525  1.685741739      4              2           4             0             2
## 526  2.017033339      4              2           4             0             2
## 527  0.550228353      3              1           4             1             2
## 528  1.672097858      2              2           2             0             0
## 529  2.190331698      4              4           4             0             0
## 530  0.532754379      2              2           3             1             0
## 531  0.651278014      2              2           1            -1             0
## 532  1.664641976      2              2           2             0             0
## 533  0.474216264      0              3           1             1            -3
## 534  0.492760389      2              3           2             0            -1
## 535  1.951823035      2              2           2             0             0
## 536  1.367355921      2              2           2             0             0
## 537  0.481442629      1              1           1             0             0
## 538  0.820857989     NA             NA          NA            NA            NA
## 539  0.820201459      1              1           1             0             0
## 540  1.382017043      3              3           2            -1             0
## 541  2.950851459      4              4           3            -1             0
## 542  3.071882007      5              5           5             0             0
## 543  1.596597096      4              2           2            -2             2
## 544  2.113943352      2              3           2             0            -1
## 545  2.600972896      4              4           1            -3             0
## 546  0.945960704      2              3           1            -1            -1
## 547  1.267171728      2              2           2             0             0
## 548  2.725094521      3              3           3             0             0
## 549  2.634477270      3              4           4             1            -1
## 550  1.488550717      3              3           3             0             0
## 551  1.791690649      2              2           2             0             0
## 552  0.956648579      2              1           2             0             1
## 553 -0.193820026     NA             NA          NA            NA            NA
## 554  0.149219113      1              1           1             0             0
## 555  1.336459734      2              2           2             0             0
## 556  1.683047038      4              4           4             0             0
## 557  0.068185862      1              2           1             0            -1
## 558  1.235528447      1              1           2             1             0
## 559  1.630427875      3              1           2            -1             2
## 560 -0.194499142      0              0           2             2             0
## 561  0.274157849     NA             NA          NA            NA            NA
## 562  1.367355921      1              2           2             1            -1
## 563  1.158362492      2              2           2             0             0
## 564  0.371067862      2              1           1            -1             1
## 565  0.691081492      1              1           1             0             0
## 566 -0.065501549     NA             NA          NA            NA            NA
## 567  0.178976947     NA             NA          NA            NA            NA
## 568  0.269512944      2              1           0            -2             1
## 569  3.611723308      3              3           3             0             0
## 570 -0.090979146     NA             NA          NA            NA            NA
## 571  2.561101384      2              1           2             0             1
## 572  0.000000000     NA             NA          NA            NA            NA
## 573  1.201397124      2              1           2             0             1
## 574  0.962369336      1              3           3             2            -2
## 575  1.201397124      2              0           0            -2             2
## 576  3.611723308      3              3           3             0             0
## 577  2.416640507      2              2           2             0             0
## 578  0.000000000     NA             NA          NA            NA            NA
## 579  0.311753861      2              2           2             0             0
## 580  0.311753861      3              3           3             0             0
## 581  4.378397901      4              4           4             0             0
## 582  3.611723308      3              3           2            -1             0
## 583  0.000000000      2              0           0            -2             2
## 584  3.611723308      3              3           3             0             0
## 585  1.201397124      2              2           2             0             0
## 586  0.000000000      2              2           0            -2             0
## 587  1.371067862      3              3           3             0             0
## 588  1.201397124      3              0           3             0             3
## 589  4.285557309      3              4           4             1            -1
## 590  0.000000000      2              3           2             0            -1
## 591  3.611723308      4              4           4             0             0
## 592  3.611723308      3              2           3             0             1

Now I can ask a variety of questions with this dataset. For example, lets see where epistasis changes node visitation

dim(adaptive_traj_access %>%
  drop_na() %>%
  filter(access != access_no_idio))[1] / dim(adaptive_traj_access %>% drop_na())[1]
## [1] 0.4939966
paste0(dim(adaptive_traj_access %>%
  drop_na() %>%
  filter(access != access_no_idio))[1], "/", dim(adaptive_traj_access %>% drop_na())[1])
## [1] "288/583"

How often does epistasis changes node visitation for adaptive trajectories

dim(adaptive_traj_access %>%
  filter(likely) %>%
  drop_na() %>%
  filter(access != access_no_idio))[1] / dim(adaptive_traj_access %>% filter(likely) %>% drop_na())[1]
## [1] 0.2619048
paste0(dim(adaptive_traj_access %>%
  filter(likely) %>%
  drop_na() %>%
  filter(access != access_no_idio))[1], "/", dim(adaptive_traj_access %>% filter(likely) %>% drop_na())[1])
## [1] "11/42"

Where is idiosyncratic visitation different from the mean WHEN epistasis affects node visitation?

dim(adaptive_traj_access %>%
  drop_na() %>%
  filter(access != access_mean & access != access_no_idio))[1] / dim(adaptive_traj_access %>% filter(access != access_no_idio) %>% drop_na())[1]
## [1] 0.7326389
paste0(dim(adaptive_traj_access %>%
  drop_na() %>%
  filter(access != access_mean & access != access_no_idio))[1], "/", dim(adaptive_traj_access %>% filter(access != access_no_idio) %>% drop_na())[1])
## [1] "211/288"

Where is idiosyncratic visitation different from the mean in the likely traj?

dim(adaptive_traj_access %>%
  filter(likely) %>%
  drop_na() %>%
  filter(access != access_mean))[1] / dim(adaptive_traj_access %>% filter(likely) %>% drop_na())[1]
## [1] 0.1904762
paste0(dim(adaptive_traj_access %>%
  filter(likely) %>%
  drop_na() %>%
  filter(access != access_mean))[1], "/", dim(adaptive_traj_access %>% filter(likely) %>% drop_na())[1])
## [1] "8/42"

Restrictive idiosyncrasy: When negative epistasis prevents node visitation AND mean epistasis would have allowed for it

adaptive_traj_access %>%
  drop_na() %>%
  filter(avg < log10(1/1.5) & access_w_idio < 0 & access_w_mean > 0 & means > 0)
##    genotype        avg                          pos mutations likely
## 1    xxxx00 -3.4400740               p1|p21|p26|p28         4  FALSE
## 2    x0xx0x -1.1042305               p1|p26|p28|p94         4  FALSE
## 3    0xx000 -4.0673669                      p21|p26         2  FALSE
## 4    0x0xx0 -1.6714200                  p21|p28|p30         3  FALSE
## 5    0x00x0 -0.2888077                      p21|p30         2  FALSE
## 6    0x00xx -1.5696224                  p21|p30|p94         3  FALSE
## 7    00x00x -0.7310345                      p26|p94         2  FALSE
## 8    000xxx -2.0436471                  p28|p30|p94         3  FALSE
## 9     x000x -0.8883718                     p72|p273         2  FALSE
## 10  00xxxx0 -0.1976298          p219|p222|p224|p225         4  FALSE
## 11  x0x0xx0 -0.2755877           p41|p219|p224|p225         4  FALSE
## 12  x00x0xx -0.1767230           p41|p222|p225|p227         4  FALSE
## 13  x000x00 -0.1999418                     p41|p224         2  FALSE
## 14  xxxxxx0 -0.8084870 p41|p215|p219|p222|p224|p225         6  FALSE
## 15  xxxxx0x -0.9215912 p41|p215|p219|p222|p224|p227         6  FALSE
## 16  xxx0xxx -0.7393002 p41|p215|p219|p224|p225|p227         6   TRUE
## 17  xx0xxxx -0.3881689 p41|p215|p222|p224|p225|p227         6  FALSE
## 18   0xxx0x -0.1911406          p142|p154|p158|p215         4  FALSE
## 19   0x0xxx -0.2428085          p142|p158|p180|p215         4  FALSE
## 20   00xxxx -0.3383319          p154|p158|p180|p215         4  FALSE
## 21   x0xx0x -0.3904590           p67|p154|p158|p215         4  FALSE
## 22    0xxx0 -1.6219401                p42|p104|p182         3  FALSE
##               unique_id enzyme_name measure_type      cond       means
## 1      DHFR_ic75_palmer        DHFR         ic75    palmer 0.086939990
## 2      DHFR_ic75_palmer        DHFR         ic75    palmer 2.573205564
## 3      DHFR_ic75_palmer        DHFR         ic75    palmer 0.535154647
## 4      DHFR_ic75_palmer        DHFR         ic75    palmer 0.760258028
## 5      DHFR_ic75_palmer        DHFR         ic75    palmer 0.298883333
## 6      DHFR_ic75_palmer        DHFR         ic75    palmer 0.279451613
## 7      DHFR_ic75_palmer        DHFR         ic75    palmer 0.496677313
## 8      DHFR_ic75_palmer        DHFR         ic75    palmer 0.680059180
## 9      MPH_catact_ZnPTM         MPH       catact     ZnPTM 0.602786109
## 10       NfsA_ec50_2039        NfsA         ec50      2039 0.032862709
## 11       NfsA_ec50_2039        NfsA         ec50      2039 0.051240783
## 12       NfsA_ec50_2039        NfsA         ec50      2039 0.025115068
## 13       NfsA_ec50_2039        NfsA         ec50      2039 0.058499915
## 14       NfsA_ec50_3637        NfsA         ec50      3637 0.148040734
## 15       NfsA_ec50_3637        NfsA         ec50      3637 0.034936572
## 16       NfsA_ec50_3637        NfsA         ec50      3637 0.217227524
## 17       NfsA_ec50_3637        NfsA         ec50      3637 0.568358874
## 18 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 0.164689964
## 19 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 0.017996043
## 20 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 0.078829122
## 21 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 0.004661701
## 22    TEM_MIC_weinreich         TEM          MIC weinreich 0.134901726
##    traj_effects access access_no_idio access_mean access_w_mean access_w_idio
## 1     2.3242825      3              4           4             1            -1
## 2     2.3263359      3              4           4             1            -1
## 3    -3.0315171      0              2           2             2            -2
## 4    -0.8041003      0              1           2             2            -1
## 5     0.7067178      1              2           2             1            -1
## 6    -0.5436340      0              2           2             2            -2
## 7     1.0492180      1              2           2             1            -1
## 8    -0.1573908      0              2           3             3            -2
## 9     0.7109631      1              2           2             1            -1
## 10    0.2355284      2              4           4             2            -2
## 11    0.6473830      3              4           4             1            -1
## 12    0.7126497      3              4           4             1            -1
## 13   -0.1518109      0              1           2             2            -1
## 14    0.9795484      5              6           6             1            -1
## 15    0.1553360      5              6           6             1            -1
## 16    0.9454686      5              6           6             1            -1
## 17    0.8169038      5              6           6             1            -1
## 18    0.3765770      2              3           4             2            -1
## 19    0.4608978      2              4           4             2            -2
## 20    0.4424798      1              4           4             3            -3
## 21    0.9670797      2              4           4             2            -2
## 22    0.9623693      1              3           3             2            -2

What about positive epistasis that does not affect or increases visitation?

adaptive_traj_access %>%
  drop_na() %>%
  filter(avg > log10(1.5) & access_w_idio >= 0)
##     genotype        avg                               pos mutations likely
## 1     xxx000  4.0915006                        p1|p21|p26         3  FALSE
## 2     xxxxx0  0.2127319                p1|p21|p26|p28|p30         5  FALSE
## 3     xxxx0x 10.4358638                p1|p21|p26|p28|p94         5  FALSE
## 4     xxx0xx  2.5755328                p1|p21|p26|p30|p94         5  FALSE
## 5     xx0x00  0.7938784                        p1|p21|p28         3  FALSE
## 6     xx0xx0  1.9958051                    p1|p21|p28|p30         4  FALSE
## 7     xx0xxx  3.1289862                p1|p21|p28|p30|p94         5  FALSE
## 8     xx00xx  1.3698610                    p1|p21|p30|p94         4  FALSE
## 9     xx000x  1.0635938                        p1|p21|p94         3  FALSE
## 10    x0x000  0.1951793                            p1|p26         2  FALSE
## 11    x0xxx0  0.2566377                    p1|p26|p28|p30         4  FALSE
## 12    x0xxxx  0.5135761                p1|p26|p28|p30|p94         5  FALSE
## 13    x0x0xx  0.2071172                    p1|p26|p30|p94         4  FALSE
## 14    x0x00x  0.7200699                        p1|p26|p94         3  FALSE
## 15    x00xxx  2.2307063                    p1|p28|p30|p94         4  FALSE
## 16    x00x0x  1.0706822                        p1|p28|p94         3  FALSE
## 17    x000x0  0.8028661                            p1|p30         2  FALSE
## 18    0xxx00  3.2599112                       p21|p26|p28         3  FALSE
## 19    0xxxxx  0.9545832               p21|p26|p28|p30|p94         5  FALSE
## 20    0xx0x0  3.7900357                       p21|p26|p30         3  FALSE
## 21    0xx00x  5.0316956                       p21|p26|p94         3  FALSE
## 22    0x0xxx  2.6259368                   p21|p28|p30|p94         4  FALSE
## 23    00xx0x  0.7498001                       p26|p28|p94         3  FALSE
## 24    00x0x0  0.4506381                           p26|p30         2  FALSE
## 25    0000xx  0.2248027                           p30|p94         2  FALSE
## 26     xx000  0.3307007                           p21|p26         2  FALSE
## 27     xxx00  0.3536997                       p21|p26|p28         3  FALSE
## 28     xx0xx  0.5272617                   p21|p26|p30|p94         4  FALSE
## 29     x0x00  0.2181874                           p21|p28         2  FALSE
## 30     x0xxx  1.8737920                   p21|p28|p30|p94         4  FALSE
## 31     x00x0  0.7857643                           p21|p30         2  FALSE
## 32     x000x  0.8318209                           p21|p94         2  FALSE
## 33     0xx00  0.3552586                           p26|p28         2  FALSE
## 34     0xxxx  0.3612176                   p26|p28|p30|p94         4   TRUE
## 35     0x0x0  0.6355068                           p26|p30         2  FALSE
## 36     0x00x  0.3207425                           p26|p94         2  FALSE
## 37     00xx0  0.3513283                           p28|p30         2  FALSE
## 38     00x0x  0.6093657                           p28|p94         2   TRUE
## 39     000xx  1.7722915                           p30|p94         2  FALSE
## 40     xx000  0.3307007                           p21|p26         2  FALSE
## 41     xxx00  0.3536997                       p21|p26|p28         3  FALSE
## 42     xxxx0  0.6065199                   p21|p26|p28|p30         4  FALSE
## 43     xx0xx  0.3995444                   p21|p26|p30|p94         4  FALSE
## 44     x0x00  0.2181874                           p21|p28         2  FALSE
## 45     x0xxx  1.2697737                   p21|p28|p30|p94         4  FALSE
## 46     x00x0  0.9314347                           p21|p30         2  FALSE
## 47     x000x  0.8318209                           p21|p94         2  FALSE
## 48     0xx00  0.3552586                           p26|p28         2  FALSE
## 49     0x0x0  0.5505949                           p26|p30         2  FALSE
## 50     0x0xx  0.5514262                       p26|p30|p94         3  FALSE
## 51     0x00x  0.3207425                           p26|p94         2  FALSE
## 52     00xx0  0.8108607                           p28|p30         2  FALSE
## 53     00x0x  0.6093657                           p28|p94         2   TRUE
## 54     0xxxx  0.3792063               p193|p258|p271|p273         4  FALSE
## 55     00xx0  0.3449452                         p258|p271         2  FALSE
## 56     00xxx  0.3467544                    p258|p271|p273         3  FALSE
## 57     xxx0x  0.2309903                p72|p193|p258|p273         4   TRUE
## 58     xx0xx  0.3313957                p72|p193|p271|p273         4  FALSE
## 59     xx00x  1.2255130                     p72|p193|p273         3  FALSE
## 60     x0xxx  0.4273977                p72|p258|p271|p273         4  FALSE
## 61     x0x0x  0.5030731                     p72|p258|p273         3  FALSE
## 62     x00xx  0.9335231                     p72|p271|p273         3  FALSE
## 63   0xxxxx0  0.1926166          p215|p219|p222|p224|p225         5  FALSE
## 64   0xx0x00  0.2287509                    p215|p219|p224         3  FALSE
## 65   0xx0xxx  0.5419563          p215|p219|p224|p225|p227         5  FALSE
## 66   0xx00x0  0.4841288                    p215|p219|p225         3  FALSE
## 67   0x0xxxx  0.2850142          p215|p222|p224|p225|p227         5  FALSE
## 68   0x00xx0  0.3700748                    p215|p224|p225         3  FALSE
## 69   0x000xx  0.3526148                    p215|p225|p227         3  FALSE
## 70   00xxxxx  0.2066060          p219|p222|p224|p225|p227         5  FALSE
## 71   00000xx  0.2144987                         p225|p227         2  FALSE
## 72   xxxxxxx  0.2315052 p41|p215|p219|p222|p224|p225|p227         7  FALSE
## 73   xxxxx0x  0.1907594      p41|p215|p219|p222|p224|p227         6  FALSE
## 74   xxx0xx0  0.5158592           p41|p215|p219|p224|p225         5  FALSE
## 75   xx0xxx0  0.2094495           p41|p215|p222|p224|p225         5  FALSE
## 76   xx0x0xx  0.3418076           p41|p215|p222|p225|p227         5  FALSE
## 77   xx00x00  0.2626518                     p41|p215|p224         3  FALSE
## 78   xx00xxx  0.4214522           p41|p215|p224|p225|p227         5  FALSE
## 79   xx000x0  0.6668734                     p41|p215|p225         3  FALSE
## 80   x0xxxx0  0.2249481           p41|p219|p222|p224|p225         5  FALSE
## 81   x0x0x00  0.1951751                     p41|p219|p224         3  FALSE
## 82   x0x0xxx  0.2083878           p41|p219|p224|p225|p227         5  FALSE
## 83   x00xxxx  0.2077501           p41|p222|p224|p225|p227         5  FALSE
## 84   x000xx0  0.3525577                     p41|p224|p225         3  FALSE
## 85   0xxx00x  0.3133913               p215|p219|p222|p227         4  FALSE
## 86   0xx0x0x  0.2739510               p215|p219|p224|p227         4  FALSE
## 87   0xx00x0  0.3031382                    p215|p219|p225         3  FALSE
## 88   0x0xx0x  0.2141675               p215|p222|p224|p227         4  FALSE
## 89   0x00xxx  0.3657730               p215|p224|p225|p227         4  FALSE
## 90   0x000xx  0.3965362                    p215|p225|p227         3  FALSE
## 91   0x0000x  0.2929325                         p215|p227         2  FALSE
## 92   00xx0xx  0.2335504               p219|p222|p225|p227         4  FALSE
## 93   00x0x00  0.2124097                         p219|p224         2  FALSE
## 94   000xxxx  0.4085244               p222|p224|p225|p227         4  FALSE
## 95   000x00x  0.2666392                         p222|p227         2  FALSE
## 96   0000xx0  0.3270425                         p224|p225         2  FALSE
## 97   00000xx  0.1981897                         p225|p227         2  FALSE
## 98   xxxxxxx  1.9130555 p41|p215|p219|p222|p224|p225|p227         7   TRUE
## 99   xxxx0x0  0.3058285           p41|p215|p219|p222|p225         5  FALSE
## 100  xxxx00x  0.7515982           p41|p215|p219|p222|p227         5  FALSE
## 101  xxx0xx0  0.2205264           p41|p215|p219|p224|p225         5  FALSE
## 102  xxx0x0x  0.5787185           p41|p215|p219|p224|p227         5  FALSE
## 103  xxx00xx  0.4055680           p41|p215|p219|p225|p227         5  FALSE
## 104  xx0xx0x  0.4530458           p41|p215|p222|p224|p227         5  FALSE
## 105  xx0x0xx  0.7581143           p41|p215|p222|p225|p227         5  FALSE
## 106  xx00xxx  0.4101789           p41|p215|p224|p225|p227         5  FALSE
## 107  xx000x0  0.6177405                     p41|p215|p225         3  FALSE
## 108  xx0000x  0.4412514                     p41|p215|p227         3  FALSE
## 109  x0xxxx0  0.4244484           p41|p219|p222|p224|p225         5  FALSE
## 110  x0xxx0x  0.7129843           p41|p219|p222|p224|p227         5  FALSE
## 111  x0xx0xx  0.6719119           p41|p219|p222|p225|p227         5  FALSE
## 112  x0x0xxx  0.9140294           p41|p219|p224|p225|p227         5   TRUE
## 113  x0x000x  0.6297636                     p41|p219|p227         3  FALSE
## 114  x00xxx0  0.3133401                p41|p222|p224|p225         4  FALSE
## 115  x00xxxx  0.3339212           p41|p222|p224|p225|p227         5  FALSE
## 116  x00x00x  0.4093652                     p41|p222|p227         3  FALSE
## 117  x000x0x  0.5949846                     p41|p224|p227         3  FALSE
## 118  x0000xx  0.3800391                     p41|p225|p227         3  FALSE
## 119     00xx  0.2092675                         p212|p213         2  FALSE
## 120     xxxx  0.2724234                 p33|p72|p212|p213         4   TRUE
## 121     0xx0  0.6098199                          p72|p212         2  FALSE
## 122     0x0x  0.8038499                          p72|p213         2   TRUE
## 123   00xx0x  0.3996077                    p124|p132|p243         3  FALSE
## 124   00x00x  0.2493602                         p124|p243         2  FALSE
## 125   000xxx  0.2022888                    p132|p156|p243         3  FALSE
## 126   0000xx  0.2453667                         p156|p243         2  FALSE
## 127   x0xx00  0.2129063                     p66|p124|p132         3  FALSE
## 128   x0x0xx  0.4265923                p66|p124|p156|p243         4  FALSE
## 129   xxxxxx  0.2371716       p66|p76|p124|p132|p156|p243         6   TRUE
## 130   xxx0x0  0.1837956                 p66|p76|p124|p156         4  FALSE
## 131   xxx00x  0.3693714                 p66|p76|p124|p243         4  FALSE
## 132   xx00x0  0.1813204                      p66|p76|p156         3  FALSE
## 133   xx00xx  0.3471839                 p66|p76|p156|p243         4  FALSE
## 134   0xx000  0.3089057                          p76|p124         2  FALSE
## 135   0xxxx0  0.2279391                p76|p124|p132|p156         4  FALSE
## 136   0xx0xx  0.3817072                p76|p124|p156|p243         4   TRUE
## 137   0x000x  0.2491061                          p76|p243         2  FALSE
## 138   0xxxxx  0.4960242          p142|p154|p158|p180|p215         5  FALSE
## 139   000xxx  0.1923837                    p158|p180|p215         3  FALSE
## 140   xxxx0x  0.4519437           p67|p142|p154|p158|p215         5  FALSE
## 141   xxx0x0  0.2375477                p67|p142|p154|p180         4  FALSE
## 142   xx0x00  0.2148131                     p67|p142|p158         3   TRUE
## 143   xx0xxx  0.2618915           p67|p142|p158|p180|p215         5  FALSE
## 144   xx000x  0.2179967                     p67|p142|p215         3  FALSE
## 145   x0xxxx  0.5746045           p67|p154|p158|p180|p215         5  FALSE
## 146   x00x00  0.5040028                          p67|p158         2   TRUE
## 147   x00xx0  0.1772274                     p67|p158|p180         3  FALSE
## 148   x00x0x  0.2813481                     p67|p158|p215         3  FALSE
## 149   xx0000  1.2829707                         p233|p254         2  FALSE
## 150   xxxx00  0.1965328               p233|p254|p271|p272         4  FALSE
## 151   xxxxxx  0.2725240     p233|p254|p271|p272|p306|p313         6  FALSE
## 152   xxx0x0  0.8786927               p233|p254|p271|p306         4   TRUE
## 153   xxx00x  0.9425507               p233|p254|p271|p313         4  FALSE
## 154   xx0xxx  0.4836946          p233|p254|p272|p306|p313         5  FALSE
## 155   xx0x0x  0.4066111               p233|p254|p272|p313         4  FALSE
## 156   xx00xx  0.6635153               p233|p254|p306|p313         4  FALSE
## 157   x0xxx0  0.2559400               p233|p271|p272|p306         4  FALSE
## 158   x0xxxx  0.6985225          p233|p271|p272|p306|p313         5  FALSE
## 159   x0xx0x  0.2886868               p233|p271|p272|p313         4  FALSE
## 160   x000xx  0.2113048                    p233|p306|p313         3  FALSE
## 161   0xx000  0.1931635                         p254|p271         2  FALSE
## 162   0xxx0x  0.2459981               p254|p271|p272|p313         4  FALSE
## 163   0x0xx0  0.3960234                    p254|p272|p306         3  FALSE
## 164   0x000x  0.2012921                         p254|p313         2  FALSE
## 165   00x0xx  1.0589513                    p271|p306|p313         3  FALSE
## 166   000xxx  0.3574693                    p272|p306|p313         3  FALSE
## 167    00xx0  0.1815151                         p104|p182         2  FALSE
## 168    00x0x  2.2313492                         p104|p238         2   TRUE
## 169    000xx  1.4506834                         p182|p238         2  FALSE
## 170    0xx00  1.0224202                          p42|p104         2  FALSE
## 171    0xxxx  1.9266776                p42|p104|p182|p238         4   TRUE
## 172    0x0x0  1.2923763                          p42|p182         2  FALSE
## 173    0x00x  1.2152434                          p42|p238         2  FALSE
## 174    x00xx  0.9596428                   p4205|p182|p238         3  FALSE
## 175    xxxx0  1.4522693               p4205|p42|p104|p182         4  FALSE
## 176    xxxxx  0.2694734          p4205|p42|p104|p182|p238         5   TRUE
## 177    xx00x  1.1950828                    p4205|p42|p238         3  FALSE
##                unique_id enzyme_name measure_type      cond        means
## 1       DHFR_ic75_palmer        DHFR         ic75    palmer  0.217216184
## 2       DHFR_ic75_palmer        DHFR         ic75    palmer -3.381835882
## 3       DHFR_ic75_palmer        DHFR         ic75    palmer  6.841295986
## 4       DHFR_ic75_palmer        DHFR         ic75    palmer -1.019035014
## 5       DHFR_ic75_palmer        DHFR         ic75    palmer  0.010454317
## 6       DHFR_ic75_palmer        DHFR         ic75    palmer  1.869380289
## 7       DHFR_ic75_palmer        DHFR         ic75    palmer -0.465581551
## 8       DHFR_ic75_palmer        DHFR         ic75    palmer  2.424836638
## 9       DHFR_ic75_palmer        DHFR         ic75    palmer -0.373479384
## 10      DHFR_ic75_palmer        DHFR         ic75    palmer  0.215500788
## 11      DHFR_ic75_palmer        DHFR         ic75    palmer -1.177492205
## 12      DHFR_ic75_palmer        DHFR         ic75    palmer -3.080991709
## 13      DHFR_ic75_palmer        DHFR         ic75    palmer -0.045612248
## 14      DHFR_ic75_palmer        DHFR         ic75    palmer  0.102700261
## 15      DHFR_ic75_palmer        DHFR         ic75    palmer  2.254703577
## 16      DHFR_ic75_palmer        DHFR         ic75    palmer  1.647841559
## 17      DHFR_ic75_palmer        DHFR         ic75    palmer  0.695195042
## 18      DHFR_ic75_palmer        DHFR         ic75    palmer  1.124524104
## 19      DHFR_ic75_palmer        DHFR         ic75    palmer -2.639984560
## 20      DHFR_ic75_palmer        DHFR         ic75    palmer  0.947297526
## 21      DHFR_ic75_palmer        DHFR         ic75    palmer  1.695299221
## 22      DHFR_ic75_palmer        DHFR         ic75    palmer  2.870437650
## 23      DHFR_ic75_palmer        DHFR         ic75    palmer -0.043087603
## 24      DHFR_ic75_palmer        DHFR         ic75    palmer  0.352814894
## 25      DHFR_ic75_palmer        DHFR         ic75    palmer -0.563214885
## 26         DHFR_ki_trajg        DHFR           ki     trajg  0.410912753
## 27         DHFR_ki_trajg        DHFR           ki     trajg  0.082006660
## 28         DHFR_ki_trajg        DHFR           ki     trajg  0.326060583
## 29         DHFR_ki_trajg        DHFR           ki     trajg  0.077303838
## 30         DHFR_ki_trajg        DHFR           ki     trajg  1.672590918
## 31         DHFR_ki_trajg        DHFR           ki     trajg  0.214034606
## 32         DHFR_ki_trajg        DHFR           ki     trajg  0.015658816
## 33         DHFR_ki_trajg        DHFR           ki     trajg  0.402406020
## 34         DHFR_ki_trajg        DHFR           ki     trajg  0.160016473
## 35         DHFR_ki_trajg        DHFR           ki     trajg  0.418956845
## 36         DHFR_ki_trajg        DHFR           ki     trajg  0.256944120
## 37         DHFR_ki_trajg        DHFR           ki     trajg -0.277507064
## 38         DHFR_ki_trajg        DHFR           ki     trajg -0.297834483
## 39         DHFR_ki_trajg        DHFR           ki     trajg  0.535607716
## 40         DHFR_ki_trajr        DHFR           ki     trajr  0.239167595
## 41         DHFR_ki_trajr        DHFR           ki     trajr  0.445570792
## 42         DHFR_ki_trajr        DHFR           ki     trajr  0.357234391
## 43         DHFR_ki_trajr        DHFR           ki     trajr  0.150258886
## 44         DHFR_ki_trajr        DHFR           ki     trajr -0.146072962
## 45         DHFR_ki_trajr        DHFR           ki     trajr  1.020488239
## 46         DHFR_ki_trajr        DHFR           ki     trajr  0.242098088
## 47         DHFR_ki_trajr        DHFR           ki     trajr  0.280000986
## 48         DHFR_ki_trajr        DHFR           ki     trajr  0.092249759
## 49         DHFR_ki_trajr        DHFR           ki     trajr  0.126911640
## 50         DHFR_ki_trajr        DHFR           ki     trajr  0.407566173
## 51         DHFR_ki_trajr        DHFR           ki     trajr  0.469744755
## 52         DHFR_ki_trajr        DHFR           ki     trajr  0.048558239
## 53         DHFR_ki_trajr        DHFR           ki     trajr -0.078811299
## 54      MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.029835956
## 55      MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.575971300
## 56      MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.575371168
## 57      MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.118379979
## 58      MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.017974583
## 59      MPH_catact_ZnPTM         MPH       catact     ZnPTM  1.332020910
## 60      MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.078027364
## 61      MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.657581922
## 62      MPH_catact_ZnPTM         MPH       catact     ZnPTM  1.138234602
## 63        NfsA_ec50_2039        NfsA         ec50      2039  0.091641808
## 64        NfsA_ec50_2039        NfsA         ec50      2039 -0.036461257
## 65        NfsA_ec50_2039        NfsA         ec50      2039  0.245504340
## 66        NfsA_ec50_2039        NfsA         ec50      2039  0.351777786
## 67        NfsA_ec50_2039        NfsA         ec50      2039  0.042804203
## 68        NfsA_ec50_2039        NfsA         ec50      2039 -0.017781959
## 69        NfsA_ec50_2039        NfsA         ec50      2039  0.139765328
## 70        NfsA_ec50_2039        NfsA         ec50      2039  0.091283562
## 71        NfsA_ec50_2039        NfsA         ec50      2039  0.288989481
## 72        NfsA_ec50_2039        NfsA         ec50      2039  0.231505206
## 73        NfsA_ec50_2039        NfsA         ec50      2039  0.306511983
## 74        NfsA_ec50_2039        NfsA         ec50      2039  0.282532026
## 75        NfsA_ec50_2039        NfsA         ec50      2039  0.030364300
## 76        NfsA_ec50_2039        NfsA         ec50      2039  0.214665214
## 77        NfsA_ec50_2039        NfsA         ec50      2039  0.089121883
## 78        NfsA_ec50_2039        NfsA         ec50      2039  0.046889824
## 79        NfsA_ec50_2039        NfsA         ec50      2039  0.528651949
## 80        NfsA_ec50_2039        NfsA         ec50      2039  0.172750482
## 81        NfsA_ec50_2039        NfsA         ec50      2039  0.051632061
## 82        NfsA_ec50_2039        NfsA         ec50      2039 -0.039287044
## 83        NfsA_ec50_2039        NfsA         ec50      2039  0.014317246
## 84        NfsA_ec50_2039        NfsA         ec50      2039  0.170826259
## 85        NfsA_ec50_3637        NfsA         ec50      3637  0.160300084
## 86        NfsA_ec50_3637        NfsA         ec50      3637  0.092614626
## 87        NfsA_ec50_3637        NfsA         ec50      3637  0.218717203
## 88        NfsA_ec50_3637        NfsA         ec50      3637  0.012205919
## 89        NfsA_ec50_3637        NfsA         ec50      3637  0.104497453
## 90        NfsA_ec50_3637        NfsA         ec50      3637  0.168111203
## 91        NfsA_ec50_3637        NfsA         ec50      3637  0.187697910
## 92        NfsA_ec50_3637        NfsA         ec50      3637  0.061186698
## 93        NfsA_ec50_3637        NfsA         ec50      3637  0.074854163
## 94        NfsA_ec50_3637        NfsA         ec50      3637  0.167571165
## 95        NfsA_ec50_3637        NfsA         ec50      3637  0.063311553
## 96        NfsA_ec50_3637        NfsA         ec50      3637  0.312612193
## 97        NfsA_ec50_3637        NfsA         ec50      3637  0.052353689
## 98        NfsA_ec50_3637        NfsA         ec50      3637  1.913055479
## 99        NfsA_ec50_3637        NfsA         ec50      3637 -0.182582709
## 100       NfsA_ec50_3637        NfsA         ec50      3637  0.206634861
## 101       NfsA_ec50_3637        NfsA         ec50      3637 -0.075103365
## 102       NfsA_ec50_3637        NfsA         ec50      3637  0.226536706
## 103       NfsA_ec50_3637        NfsA         ec50      3637 -0.048249881
## 104       NfsA_ec50_3637        NfsA         ec50      3637  0.276429636
## 105       NfsA_ec50_3637        NfsA         ec50      3637  0.479862128
## 106       NfsA_ec50_3637        NfsA         ec50      3637  0.324708216
## 107       NfsA_ec50_3637        NfsA         ec50      3637  0.209513563
## 108       NfsA_ec50_3637        NfsA         ec50      3637 -0.181880262
## 109       NfsA_ec50_3637        NfsA         ec50      3637 -0.198513642
## 110       NfsA_ec50_3637        NfsA         ec50      3637  0.033470171
## 111       NfsA_ec50_3637        NfsA         ec50      3637 -0.109238294
## 112       NfsA_ec50_3637        NfsA         ec50      3637  0.325660765
## 113       NfsA_ec50_3637        NfsA         ec50      3637  0.224891005
## 114       NfsA_ec50_3637        NfsA         ec50      3637  0.246350434
## 115       NfsA_ec50_3637        NfsA         ec50      3637 -0.078881834
## 116       NfsA_ec50_3637        NfsA         ec50      3637 -0.055554618
## 117       NfsA_ec50_3637        NfsA         ec50      3637  0.120640826
## 118       NfsA_ec50_3637        NfsA         ec50      3637 -0.360855472
## 119 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.001843610
## 120 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.272423449
## 121 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.452007376
## 122 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.529802289
## 123 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.077667202
## 124 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.146937967
## 125 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.024577444
## 126 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.037403037
## 127 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.155031553
## 128 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.386238225
## 129 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.237171612
## 130 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.002308696
## 131 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.233908794
## 132 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.310315577
## 133 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.100521064
## 134 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.268755433
## 135 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.120377866
## 136 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.230852093
## 137 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.197798300
## 138 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.259717480
## 139 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.041536847
## 140 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.215636991
## 141 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.164932025
## 142 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.174011928
## 143 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.025584752
## 144 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.072315748
## 145 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.338297731
## 146 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.662941716
## 147 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.010609253
## 148 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.121161418
## 149       PTE_catact_2NH         PTE       catact       2NH  0.637336423
## 150       PTE_catact_2NH         PTE       catact       2NH -0.495675095
## 151       PTE_catact_2NH         PTE       catact       2NH  0.272524024
## 152       PTE_catact_2NH         PTE       catact       2NH -0.333523949
## 153       PTE_catact_2NH         PTE       catact       2NH -0.226875448
## 154       PTE_catact_2NH         PTE       catact       2NH  0.619956569
## 155       PTE_catact_2NH         PTE       catact       2NH  0.357815158
## 156       PTE_catact_2NH         PTE       catact       2NH  0.094710621
## 157       PTE_catact_2NH         PTE       catact       2NH  0.271767578
## 158       PTE_catact_2NH         PTE       catact       2NH  0.834784556
## 159       PTE_catact_2NH         PTE       catact       2NH  0.347304857
## 160       PTE_catact_2NH         PTE       catact       2NH -0.059630116
## 161       PTE_catact_2NH         PTE       catact       2NH  0.013758529
## 162       PTE_catact_2NH         PTE       catact       2NH -0.230150706
## 163       PTE_catact_2NH         PTE       catact       2NH  0.175202752
## 164       PTE_catact_2NH         PTE       catact       2NH  0.102229722
## 165       PTE_catact_2NH         PTE       catact       2NH  0.476490309
## 166       PTE_catact_2NH         PTE       catact       2NH -0.094957390
## 167    TEM_MIC_weinreich         TEM          MIC weinreich -0.638009314
## 168    TEM_MIC_weinreich         TEM          MIC weinreich  0.817397805
## 169    TEM_MIC_weinreich         TEM          MIC weinreich  0.682809629
## 170    TEM_MIC_weinreich         TEM          MIC weinreich  0.041619164
## 171    TEM_MIC_weinreich         TEM          MIC weinreich  2.061414245
## 172    TEM_MIC_weinreich         TEM          MIC weinreich -0.253191980
## 173    TEM_MIC_weinreich         TEM          MIC weinreich  0.294608579
## 174    TEM_MIC_weinreich         TEM          MIC weinreich  0.499130803
## 175    TEM_MIC_weinreich         TEM          MIC weinreich  1.587006009
## 176    TEM_MIC_weinreich         TEM          MIC weinreich  0.269473383
## 177    TEM_MIC_weinreich         TEM          MIC weinreich  0.123378311
##     traj_effects access access_no_idio access_mean access_w_mean access_w_idio
## 1     1.91062440      3              1           1            -2             2
## 2     2.10380372      0              0           0             0             0
## 3     2.29446623      3              0           1            -2             3
## 4     2.31386722      5              0           0            -5             5
## 5     2.07188201      3              1           1            -2             2
## 6     2.18469143      3              1           2            -1             2
## 7     2.27875360      4              2           2            -2             2
## 8     1.71096312      1              1           4             3             0
## 9     1.98317507      3              1           0            -3             2
## 10    1.14612804      2              2           2             0             0
## 11    2.32221929      3              0           0            -3             3
## 12    2.32428246      4              1           0            -4             3
## 13    2.21748394      4              1           1            -3             3
## 14    2.04921802      3              2           2            -1             1
## 15    2.31175386      3              1           4             1             2
## 16    2.28330123      3              0           3             0             3
## 17    1.71349054      2              2           2             0             0
## 18    0.71767050      1              1           1             0             0
## 19   -0.79860288      1              1           0            -1             0
## 20    1.18752072      3              1           1            -2             2
## 21    1.36361198      3              0           1            -2             3
## 22   -3.03151705      0              0           0             0             0
## 23    2.04921802      2              1           1            -1             1
## 24    1.02530587      2              2           2             0             0
## 25    1.96473092      2              2           1            -1             0
## 26    1.02530587      2              2           2             0             0
## 27    3.08278537      3              3           3             0             0
## 28    4.65896484      4              4           4             0             0
## 29    1.70070372      2              2           2             0             0
## 30    4.19865709      4              0           4             0             4
## 31    1.48429984      2              2           2             0             0
## 32    1.80413943      2              2           2             0             0
## 33    1.82801506      2              2           2             0             0
## 34    4.58206336      4              4           4             0             0
## 35    1.32428246      2              2           2             0             0
## 36    1.28330123      2              2           2             0             0
## 37    1.82801506      2              2           2             0             0
## 38    2.35983548      2              2           2             0             0
## 39    2.73878056      2              2           2             0             0
## 40    1.02530587      2              2           2             0             0
## 41    3.08278537      3              3           3             0             0
## 42    3.96236934      4              4           4             0             0
## 43    4.11727130      4              4           4             0             0
## 44    1.70070372      2              2           2             0             0
## 45    4.11058971      4              2           4             0             2
## 46    1.64345268      2              2           2             0             0
## 47    1.80413943      2              2           2             0             0
## 48    1.82801506      2              2           2             0             0
## 49    1.25285303      2              2           2             0             0
## 50    2.84073323      3              3           3             0             0
## 51    1.28330123      2              2           2             0             0
## 52    2.30103000      2              2           2             0             0
## 53    2.35983548      2              2           2             0             0
## 54    1.10720997      3              1           2            -1             2
## 55    0.55145000      1              1           1             0             0
## 56    0.85793526      2              1           3             1             1
## 57    2.31175386      4              3           3            -1             1
## 58    2.07918125      3              3           3             0             0
## 59    2.20411998      3              1           3             0             2
## 60    1.39269695      4              4           4             0             0
## 61    0.70842090      0              0           1             1             0
## 62    0.34830486      2              0           2             0             2
## 63   -0.45593196      1              1           1             0             0
## 64   -0.13135556      2              0           0            -2             2
## 65    0.26007139      3              1           3             0             2
## 66   -0.08144547      2              0           1            -1             2
## 67   -0.36855623      1              1           1             0             0
## 68   -0.54211810      0              0           0             0             0
## 69    0.03742650      2              1           1            -1             1
## 70    0.53781910      4              2           2            -2             2
## 71    0.58206336      2              1           2             0             1
## 72    0.97909290      7              4           7             0             3
## 73   -0.14448084      2              0           4             2             2
## 74    0.75891189      4              2           3            -1             2
## 75    0.43456890      4              2           2            -2             2
## 76    0.75204845      4              3           3            -1             1
## 77   -0.07160415      2              0           0            -2             2
## 78    0.66838592      4              2           2            -2             2
## 79    0.41329976      2              1           2             0             1
## 80    0.66181269      4              2           3            -1             2
## 81    0.04139269      2              0           1            -1             2
## 82    0.86746749      5              4           2            -3             1
## 83    0.65417654      4              2           2            -2             2
## 84    0.56229286      2              1           2             0             1
## 85    0.11394335      2              0           1            -1             2
## 86   -0.10790540      2              0           0            -2             2
## 87    0.02938378      2              1           1            -1             1
## 88   -0.07160415      2              0           0            -2             2
## 89    0.55750720      4              2           2            -2             2
## 90    0.48144263      2              1           2             0             1
## 91    0.14301480      2              0           2             0             2
## 92    0.66745295      4              1           2            -2             3
## 93   -0.10182352      1              0           1             0             1
## 94    0.66558099      4              1           2            -2             3
## 95    0.20951501      2              1           1            -1             1
## 96    0.50514998      2              1           2             0             1
## 97    0.59988307      2              1           1            -1             1
## 98    1.00432137      7              0           7             0             7
## 99    0.93500315      5              3           2            -3             2
## 100   0.72345567      5              0           2            -3             5
## 101   0.94151143      5              5           2            -3             0
## 102   0.10380372      4              0           0            -4             4
## 103   0.83632412      4              1           1            -3             3
## 104  -0.01863449      3              0           0            -3             3
## 105   0.85186960      5              0           2            -3             5
## 106   0.80345712      4              1           3            -1             3
## 107   0.58206336      2              1           2             0             1
## 108   0.31386722      3              1           1            -2             2
## 109   1.00000000      5              1           1            -4             4
## 110   0.10720997      4              0           0            -4             4
## 111   0.88309336      4              0           0            -4             4
## 112   0.95664858      5              1           1            -4             4
## 113   0.27875360      3              1           1            -2             2
## 114   0.78675142      4              1           2            -2             3
## 115   0.80071708      5              1           1            -4             4
## 116   0.34830486      3              1           1            -2             2
## 117  -0.01637371      3              0           0            -3             3
## 118   0.74272513      3              1           1            -2             2
## 119   0.26481782      2              1           1            -1             1
## 120   1.60422605      4              3           4             0             1
## 121   1.04139269      2              2           2             0             0
## 122   1.13987909      2              1           2             0             1
## 123   1.14612804      3              2           3             0             1
## 124   0.77305469      2              2           2             0             0
## 125   1.04139269      3              3           3             0             0
## 126   0.77085201      2              2           2             0             0
## 127   0.46239800      3              2           2            -1             1
## 128   0.23804610      2              0           1            -1             2
## 129   1.50785587      5              4           5             0             1
## 130   0.71349054      3              2           2            -1             1
## 131   0.91539984      3              3           3             0             0
## 132   0.57054294      3              2           3             0             1
## 133   0.84010609      3              2           3             0             1
## 134   0.68394713      2              1           2             0             1
## 135   1.11394335      4              3           4             0             1
## 136   1.52762990      4              3           4             0             1
## 137   0.38021124      2              1           2             0             1
## 138   0.50105926      4              0           1            -3             4
## 139   0.48144263      3              1           1            -2             2
## 140   1.23299611      4              2           3            -1             2
## 141   0.11727130      3              0           2            -1             3
## 142   1.33645973      3              3           3             0             0
## 143   1.27646180      3              2           2            -1             1
## 144   0.20139712      3              1           2            -1             2
## 145   1.11058971      4              2           2            -2             2
## 146   0.99387691      2              2           2             0             0
## 147   1.07188201      3              2           2            -1             1
## 148   1.14921911      3              2           2            -1             1
## 149   2.71767050      2              2           2             0             0
## 150   2.79934055      3              3           2            -1             0
## 151   2.99913054      1              1           1             0             0
## 152   3.24054925      4              2           1            -3             2
## 153   2.83122969      4              2           2            -2             2
## 154   3.00000000      4              1           5             1             3
## 155   2.68574174      3              3           3             0             0
## 156   2.81224470      3              2           3             0             1
## 157   1.68574174      4              2           4             0             2
## 158   2.01703334      4              2           4             0             2
## 159   0.55022835      3              1           4             1             2
## 160   1.36735592      2              2           2             0             0
## 161   0.82020146      1              1           1             0             0
## 162   1.59659710      4              2           2            -2             2
## 163   2.72509452      3              3           3             0             0
## 164   0.95664858      2              1           2             0             1
## 165   1.63042788      3              1           2            -1             2
## 166   1.15836249      2              2           2             0             0
## 167   0.26951294      2              1           0            -2             1
## 168   3.61172331      2              2           2             0             0
## 169   2.56110138      2              1           2             0             1
## 170   1.20139712      2              1           2             0             1
## 171   4.51851394      4              1           4             0             3
## 172   1.20139712      2              0           0            -2             2
## 173   2.41664051      2              2           2             0             0
## 174   3.61172331      3              3           3             0             0
## 175   1.20139712      3              0           3             0             3
## 176   4.66838592      5              4           5             0             1
## 177   3.61172331      3              2           3             0             1
adaptive_traj_access %>%
  drop_na() %>%
  filter(avg > log10(1.5) & access_w_idio > 0)
##     genotype        avg                               pos mutations likely
## 1     xxx000  4.0915006                        p1|p21|p26         3  FALSE
## 2     xxxx0x 10.4358638                p1|p21|p26|p28|p94         5  FALSE
## 3     xxx0xx  2.5755328                p1|p21|p26|p30|p94         5  FALSE
## 4     xx0x00  0.7938784                        p1|p21|p28         3  FALSE
## 5     xx0xx0  1.9958051                    p1|p21|p28|p30         4  FALSE
## 6     xx0xxx  3.1289862                p1|p21|p28|p30|p94         5  FALSE
## 7     xx000x  1.0635938                        p1|p21|p94         3  FALSE
## 8     x0xxx0  0.2566377                    p1|p26|p28|p30         4  FALSE
## 9     x0xxxx  0.5135761                p1|p26|p28|p30|p94         5  FALSE
## 10    x0x0xx  0.2071172                    p1|p26|p30|p94         4  FALSE
## 11    x0x00x  0.7200699                        p1|p26|p94         3  FALSE
## 12    x00xxx  2.2307063                    p1|p28|p30|p94         4  FALSE
## 13    x00x0x  1.0706822                        p1|p28|p94         3  FALSE
## 14    0xx0x0  3.7900357                       p21|p26|p30         3  FALSE
## 15    0xx00x  5.0316956                       p21|p26|p94         3  FALSE
## 16    00xx0x  0.7498001                       p26|p28|p94         3  FALSE
## 17     x0xxx  1.8737920                   p21|p28|p30|p94         4  FALSE
## 18     x0xxx  1.2697737                   p21|p28|p30|p94         4  FALSE
## 19     0xxxx  0.3792063               p193|p258|p271|p273         4  FALSE
## 20     00xxx  0.3467544                    p258|p271|p273         3  FALSE
## 21     xxx0x  0.2309903                p72|p193|p258|p273         4   TRUE
## 22     xx00x  1.2255130                     p72|p193|p273         3  FALSE
## 23     x00xx  0.9335231                     p72|p271|p273         3  FALSE
## 24   0xx0x00  0.2287509                    p215|p219|p224         3  FALSE
## 25   0xx0xxx  0.5419563          p215|p219|p224|p225|p227         5  FALSE
## 26   0xx00x0  0.4841288                    p215|p219|p225         3  FALSE
## 27   0x000xx  0.3526148                    p215|p225|p227         3  FALSE
## 28   00xxxxx  0.2066060          p219|p222|p224|p225|p227         5  FALSE
## 29   00000xx  0.2144987                         p225|p227         2  FALSE
## 30   xxxxxxx  0.2315052 p41|p215|p219|p222|p224|p225|p227         7  FALSE
## 31   xxxxx0x  0.1907594      p41|p215|p219|p222|p224|p227         6  FALSE
## 32   xxx0xx0  0.5158592           p41|p215|p219|p224|p225         5  FALSE
## 33   xx0xxx0  0.2094495           p41|p215|p222|p224|p225         5  FALSE
## 34   xx0x0xx  0.3418076           p41|p215|p222|p225|p227         5  FALSE
## 35   xx00x00  0.2626518                     p41|p215|p224         3  FALSE
## 36   xx00xxx  0.4214522           p41|p215|p224|p225|p227         5  FALSE
## 37   xx000x0  0.6668734                     p41|p215|p225         3  FALSE
## 38   x0xxxx0  0.2249481           p41|p219|p222|p224|p225         5  FALSE
## 39   x0x0x00  0.1951751                     p41|p219|p224         3  FALSE
## 40   x0x0xxx  0.2083878           p41|p219|p224|p225|p227         5  FALSE
## 41   x00xxxx  0.2077501           p41|p222|p224|p225|p227         5  FALSE
## 42   x000xx0  0.3525577                     p41|p224|p225         3  FALSE
## 43   0xxx00x  0.3133913               p215|p219|p222|p227         4  FALSE
## 44   0xx0x0x  0.2739510               p215|p219|p224|p227         4  FALSE
## 45   0xx00x0  0.3031382                    p215|p219|p225         3  FALSE
## 46   0x0xx0x  0.2141675               p215|p222|p224|p227         4  FALSE
## 47   0x00xxx  0.3657730               p215|p224|p225|p227         4  FALSE
## 48   0x000xx  0.3965362                    p215|p225|p227         3  FALSE
## 49   0x0000x  0.2929325                         p215|p227         2  FALSE
## 50   00xx0xx  0.2335504               p219|p222|p225|p227         4  FALSE
## 51   00x0x00  0.2124097                         p219|p224         2  FALSE
## 52   000xxxx  0.4085244               p222|p224|p225|p227         4  FALSE
## 53   000x00x  0.2666392                         p222|p227         2  FALSE
## 54   0000xx0  0.3270425                         p224|p225         2  FALSE
## 55   00000xx  0.1981897                         p225|p227         2  FALSE
## 56   xxxxxxx  1.9130555 p41|p215|p219|p222|p224|p225|p227         7   TRUE
## 57   xxxx0x0  0.3058285           p41|p215|p219|p222|p225         5  FALSE
## 58   xxxx00x  0.7515982           p41|p215|p219|p222|p227         5  FALSE
## 59   xxx0x0x  0.5787185           p41|p215|p219|p224|p227         5  FALSE
## 60   xxx00xx  0.4055680           p41|p215|p219|p225|p227         5  FALSE
## 61   xx0xx0x  0.4530458           p41|p215|p222|p224|p227         5  FALSE
## 62   xx0x0xx  0.7581143           p41|p215|p222|p225|p227         5  FALSE
## 63   xx00xxx  0.4101789           p41|p215|p224|p225|p227         5  FALSE
## 64   xx000x0  0.6177405                     p41|p215|p225         3  FALSE
## 65   xx0000x  0.4412514                     p41|p215|p227         3  FALSE
## 66   x0xxxx0  0.4244484           p41|p219|p222|p224|p225         5  FALSE
## 67   x0xxx0x  0.7129843           p41|p219|p222|p224|p227         5  FALSE
## 68   x0xx0xx  0.6719119           p41|p219|p222|p225|p227         5  FALSE
## 69   x0x0xxx  0.9140294           p41|p219|p224|p225|p227         5   TRUE
## 70   x0x000x  0.6297636                     p41|p219|p227         3  FALSE
## 71   x00xxx0  0.3133401                p41|p222|p224|p225         4  FALSE
## 72   x00xxxx  0.3339212           p41|p222|p224|p225|p227         5  FALSE
## 73   x00x00x  0.4093652                     p41|p222|p227         3  FALSE
## 74   x000x0x  0.5949846                     p41|p224|p227         3  FALSE
## 75   x0000xx  0.3800391                     p41|p225|p227         3  FALSE
## 76      00xx  0.2092675                         p212|p213         2  FALSE
## 77      xxxx  0.2724234                 p33|p72|p212|p213         4   TRUE
## 78      0x0x  0.8038499                          p72|p213         2   TRUE
## 79    00xx0x  0.3996077                    p124|p132|p243         3  FALSE
## 80    x0xx00  0.2129063                     p66|p124|p132         3  FALSE
## 81    x0x0xx  0.4265923                p66|p124|p156|p243         4  FALSE
## 82    xxxxxx  0.2371716       p66|p76|p124|p132|p156|p243         6   TRUE
## 83    xxx0x0  0.1837956                 p66|p76|p124|p156         4  FALSE
## 84    xx00x0  0.1813204                      p66|p76|p156         3  FALSE
## 85    xx00xx  0.3471839                 p66|p76|p156|p243         4  FALSE
## 86    0xx000  0.3089057                          p76|p124         2  FALSE
## 87    0xxxx0  0.2279391                p76|p124|p132|p156         4  FALSE
## 88    0xx0xx  0.3817072                p76|p124|p156|p243         4   TRUE
## 89    0x000x  0.2491061                          p76|p243         2  FALSE
## 90    0xxxxx  0.4960242          p142|p154|p158|p180|p215         5  FALSE
## 91    000xxx  0.1923837                    p158|p180|p215         3  FALSE
## 92    xxxx0x  0.4519437           p67|p142|p154|p158|p215         5  FALSE
## 93    xxx0x0  0.2375477                p67|p142|p154|p180         4  FALSE
## 94    xx0xxx  0.2618915           p67|p142|p158|p180|p215         5  FALSE
## 95    xx000x  0.2179967                     p67|p142|p215         3  FALSE
## 96    x0xxxx  0.5746045           p67|p154|p158|p180|p215         5  FALSE
## 97    x00xx0  0.1772274                     p67|p158|p180         3  FALSE
## 98    x00x0x  0.2813481                     p67|p158|p215         3  FALSE
## 99    xxx0x0  0.8786927               p233|p254|p271|p306         4   TRUE
## 100   xxx00x  0.9425507               p233|p254|p271|p313         4  FALSE
## 101   xx0xxx  0.4836946          p233|p254|p272|p306|p313         5  FALSE
## 102   xx00xx  0.6635153               p233|p254|p306|p313         4  FALSE
## 103   x0xxx0  0.2559400               p233|p271|p272|p306         4  FALSE
## 104   x0xxxx  0.6985225          p233|p271|p272|p306|p313         5  FALSE
## 105   x0xx0x  0.2886868               p233|p271|p272|p313         4  FALSE
## 106   0xxx0x  0.2459981               p254|p271|p272|p313         4  FALSE
## 107   0x000x  0.2012921                         p254|p313         2  FALSE
## 108   00x0xx  1.0589513                    p271|p306|p313         3  FALSE
## 109    00xx0  0.1815151                         p104|p182         2  FALSE
## 110    000xx  1.4506834                         p182|p238         2  FALSE
## 111    0xx00  1.0224202                          p42|p104         2  FALSE
## 112    0xxxx  1.9266776                p42|p104|p182|p238         4   TRUE
## 113    0x0x0  1.2923763                          p42|p182         2  FALSE
## 114    xxxx0  1.4522693               p4205|p42|p104|p182         4  FALSE
## 115    xxxxx  0.2694734          p4205|p42|p104|p182|p238         5   TRUE
## 116    xx00x  1.1950828                    p4205|p42|p238         3  FALSE
##                unique_id enzyme_name measure_type      cond        means
## 1       DHFR_ic75_palmer        DHFR         ic75    palmer  0.217216184
## 2       DHFR_ic75_palmer        DHFR         ic75    palmer  6.841295986
## 3       DHFR_ic75_palmer        DHFR         ic75    palmer -1.019035014
## 4       DHFR_ic75_palmer        DHFR         ic75    palmer  0.010454317
## 5       DHFR_ic75_palmer        DHFR         ic75    palmer  1.869380289
## 6       DHFR_ic75_palmer        DHFR         ic75    palmer -0.465581551
## 7       DHFR_ic75_palmer        DHFR         ic75    palmer -0.373479384
## 8       DHFR_ic75_palmer        DHFR         ic75    palmer -1.177492205
## 9       DHFR_ic75_palmer        DHFR         ic75    palmer -3.080991709
## 10      DHFR_ic75_palmer        DHFR         ic75    palmer -0.045612248
## 11      DHFR_ic75_palmer        DHFR         ic75    palmer  0.102700261
## 12      DHFR_ic75_palmer        DHFR         ic75    palmer  2.254703577
## 13      DHFR_ic75_palmer        DHFR         ic75    palmer  1.647841559
## 14      DHFR_ic75_palmer        DHFR         ic75    palmer  0.947297526
## 15      DHFR_ic75_palmer        DHFR         ic75    palmer  1.695299221
## 16      DHFR_ic75_palmer        DHFR         ic75    palmer -0.043087603
## 17         DHFR_ki_trajg        DHFR           ki     trajg  1.672590918
## 18         DHFR_ki_trajr        DHFR           ki     trajr  1.020488239
## 19      MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.029835956
## 20      MPH_catact_ZnPTM         MPH       catact     ZnPTM  0.575371168
## 21      MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.118379979
## 22      MPH_catact_ZnPTM         MPH       catact     ZnPTM  1.332020910
## 23      MPH_catact_ZnPTM         MPH       catact     ZnPTM  1.138234602
## 24        NfsA_ec50_2039        NfsA         ec50      2039 -0.036461257
## 25        NfsA_ec50_2039        NfsA         ec50      2039  0.245504340
## 26        NfsA_ec50_2039        NfsA         ec50      2039  0.351777786
## 27        NfsA_ec50_2039        NfsA         ec50      2039  0.139765328
## 28        NfsA_ec50_2039        NfsA         ec50      2039  0.091283562
## 29        NfsA_ec50_2039        NfsA         ec50      2039  0.288989481
## 30        NfsA_ec50_2039        NfsA         ec50      2039  0.231505206
## 31        NfsA_ec50_2039        NfsA         ec50      2039  0.306511983
## 32        NfsA_ec50_2039        NfsA         ec50      2039  0.282532026
## 33        NfsA_ec50_2039        NfsA         ec50      2039  0.030364300
## 34        NfsA_ec50_2039        NfsA         ec50      2039  0.214665214
## 35        NfsA_ec50_2039        NfsA         ec50      2039  0.089121883
## 36        NfsA_ec50_2039        NfsA         ec50      2039  0.046889824
## 37        NfsA_ec50_2039        NfsA         ec50      2039  0.528651949
## 38        NfsA_ec50_2039        NfsA         ec50      2039  0.172750482
## 39        NfsA_ec50_2039        NfsA         ec50      2039  0.051632061
## 40        NfsA_ec50_2039        NfsA         ec50      2039 -0.039287044
## 41        NfsA_ec50_2039        NfsA         ec50      2039  0.014317246
## 42        NfsA_ec50_2039        NfsA         ec50      2039  0.170826259
## 43        NfsA_ec50_3637        NfsA         ec50      3637  0.160300084
## 44        NfsA_ec50_3637        NfsA         ec50      3637  0.092614626
## 45        NfsA_ec50_3637        NfsA         ec50      3637  0.218717203
## 46        NfsA_ec50_3637        NfsA         ec50      3637  0.012205919
## 47        NfsA_ec50_3637        NfsA         ec50      3637  0.104497453
## 48        NfsA_ec50_3637        NfsA         ec50      3637  0.168111203
## 49        NfsA_ec50_3637        NfsA         ec50      3637  0.187697910
## 50        NfsA_ec50_3637        NfsA         ec50      3637  0.061186698
## 51        NfsA_ec50_3637        NfsA         ec50      3637  0.074854163
## 52        NfsA_ec50_3637        NfsA         ec50      3637  0.167571165
## 53        NfsA_ec50_3637        NfsA         ec50      3637  0.063311553
## 54        NfsA_ec50_3637        NfsA         ec50      3637  0.312612193
## 55        NfsA_ec50_3637        NfsA         ec50      3637  0.052353689
## 56        NfsA_ec50_3637        NfsA         ec50      3637  1.913055479
## 57        NfsA_ec50_3637        NfsA         ec50      3637 -0.182582709
## 58        NfsA_ec50_3637        NfsA         ec50      3637  0.206634861
## 59        NfsA_ec50_3637        NfsA         ec50      3637  0.226536706
## 60        NfsA_ec50_3637        NfsA         ec50      3637 -0.048249881
## 61        NfsA_ec50_3637        NfsA         ec50      3637  0.276429636
## 62        NfsA_ec50_3637        NfsA         ec50      3637  0.479862128
## 63        NfsA_ec50_3637        NfsA         ec50      3637  0.324708216
## 64        NfsA_ec50_3637        NfsA         ec50      3637  0.209513563
## 65        NfsA_ec50_3637        NfsA         ec50      3637 -0.181880262
## 66        NfsA_ec50_3637        NfsA         ec50      3637 -0.198513642
## 67        NfsA_ec50_3637        NfsA         ec50      3637  0.033470171
## 68        NfsA_ec50_3637        NfsA         ec50      3637 -0.109238294
## 69        NfsA_ec50_3637        NfsA         ec50      3637  0.325660765
## 70        NfsA_ec50_3637        NfsA         ec50      3637  0.224891005
## 71        NfsA_ec50_3637        NfsA         ec50      3637  0.246350434
## 72        NfsA_ec50_3637        NfsA         ec50      3637 -0.078881834
## 73        NfsA_ec50_3637        NfsA         ec50      3637 -0.055554618
## 74        NfsA_ec50_3637        NfsA         ec50      3637  0.120640826
## 75        NfsA_ec50_3637        NfsA         ec50      3637 -0.360855472
## 76  OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.001843610
## 77  OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.272423449
## 78  OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1  0.529802289
## 79  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.077667202
## 80  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.155031553
## 81  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.386238225
## 82  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.237171612
## 83  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.002308696
## 84  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.310315577
## 85  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.100521064
## 86  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.268755433
## 87  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.120377866
## 88  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.230852093
## 89  OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.197798300
## 90  OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.259717480
## 91  OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.041536847
## 92  OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.215636991
## 93  OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.164932025
## 94  OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.025584752
## 95  OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.072315748
## 96  OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.338297731
## 97  OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.010609253
## 98  OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.121161418
## 99        PTE_catact_2NH         PTE       catact       2NH -0.333523949
## 100       PTE_catact_2NH         PTE       catact       2NH -0.226875448
## 101       PTE_catact_2NH         PTE       catact       2NH  0.619956569
## 102       PTE_catact_2NH         PTE       catact       2NH  0.094710621
## 103       PTE_catact_2NH         PTE       catact       2NH  0.271767578
## 104       PTE_catact_2NH         PTE       catact       2NH  0.834784556
## 105       PTE_catact_2NH         PTE       catact       2NH  0.347304857
## 106       PTE_catact_2NH         PTE       catact       2NH -0.230150706
## 107       PTE_catact_2NH         PTE       catact       2NH  0.102229722
## 108       PTE_catact_2NH         PTE       catact       2NH  0.476490309
## 109    TEM_MIC_weinreich         TEM          MIC weinreich -0.638009314
## 110    TEM_MIC_weinreich         TEM          MIC weinreich  0.682809629
## 111    TEM_MIC_weinreich         TEM          MIC weinreich  0.041619164
## 112    TEM_MIC_weinreich         TEM          MIC weinreich  2.061414245
## 113    TEM_MIC_weinreich         TEM          MIC weinreich -0.253191980
## 114    TEM_MIC_weinreich         TEM          MIC weinreich  1.587006009
## 115    TEM_MIC_weinreich         TEM          MIC weinreich  0.269473383
## 116    TEM_MIC_weinreich         TEM          MIC weinreich  0.123378311
##     traj_effects access access_no_idio access_mean access_w_mean access_w_idio
## 1     1.91062440      3              1           1            -2             2
## 2     2.29446623      3              0           1            -2             3
## 3     2.31386722      5              0           0            -5             5
## 4     2.07188201      3              1           1            -2             2
## 5     2.18469143      3              1           2            -1             2
## 6     2.27875360      4              2           2            -2             2
## 7     1.98317507      3              1           0            -3             2
## 8     2.32221929      3              0           0            -3             3
## 9     2.32428246      4              1           0            -4             3
## 10    2.21748394      4              1           1            -3             3
## 11    2.04921802      3              2           2            -1             1
## 12    2.31175386      3              1           4             1             2
## 13    2.28330123      3              0           3             0             3
## 14    1.18752072      3              1           1            -2             2
## 15    1.36361198      3              0           1            -2             3
## 16    2.04921802      2              1           1            -1             1
## 17    4.19865709      4              0           4             0             4
## 18    4.11058971      4              2           4             0             2
## 19    1.10720997      3              1           2            -1             2
## 20    0.85793526      2              1           3             1             1
## 21    2.31175386      4              3           3            -1             1
## 22    2.20411998      3              1           3             0             2
## 23    0.34830486      2              0           2             0             2
## 24   -0.13135556      2              0           0            -2             2
## 25    0.26007139      3              1           3             0             2
## 26   -0.08144547      2              0           1            -1             2
## 27    0.03742650      2              1           1            -1             1
## 28    0.53781910      4              2           2            -2             2
## 29    0.58206336      2              1           2             0             1
## 30    0.97909290      7              4           7             0             3
## 31   -0.14448084      2              0           4             2             2
## 32    0.75891189      4              2           3            -1             2
## 33    0.43456890      4              2           2            -2             2
## 34    0.75204845      4              3           3            -1             1
## 35   -0.07160415      2              0           0            -2             2
## 36    0.66838592      4              2           2            -2             2
## 37    0.41329976      2              1           2             0             1
## 38    0.66181269      4              2           3            -1             2
## 39    0.04139269      2              0           1            -1             2
## 40    0.86746749      5              4           2            -3             1
## 41    0.65417654      4              2           2            -2             2
## 42    0.56229286      2              1           2             0             1
## 43    0.11394335      2              0           1            -1             2
## 44   -0.10790540      2              0           0            -2             2
## 45    0.02938378      2              1           1            -1             1
## 46   -0.07160415      2              0           0            -2             2
## 47    0.55750720      4              2           2            -2             2
## 48    0.48144263      2              1           2             0             1
## 49    0.14301480      2              0           2             0             2
## 50    0.66745295      4              1           2            -2             3
## 51   -0.10182352      1              0           1             0             1
## 52    0.66558099      4              1           2            -2             3
## 53    0.20951501      2              1           1            -1             1
## 54    0.50514998      2              1           2             0             1
## 55    0.59988307      2              1           1            -1             1
## 56    1.00432137      7              0           7             0             7
## 57    0.93500315      5              3           2            -3             2
## 58    0.72345567      5              0           2            -3             5
## 59    0.10380372      4              0           0            -4             4
## 60    0.83632412      4              1           1            -3             3
## 61   -0.01863449      3              0           0            -3             3
## 62    0.85186960      5              0           2            -3             5
## 63    0.80345712      4              1           3            -1             3
## 64    0.58206336      2              1           2             0             1
## 65    0.31386722      3              1           1            -2             2
## 66    1.00000000      5              1           1            -4             4
## 67    0.10720997      4              0           0            -4             4
## 68    0.88309336      4              0           0            -4             4
## 69    0.95664858      5              1           1            -4             4
## 70    0.27875360      3              1           1            -2             2
## 71    0.78675142      4              1           2            -2             3
## 72    0.80071708      5              1           1            -4             4
## 73    0.34830486      3              1           1            -2             2
## 74   -0.01637371      3              0           0            -3             3
## 75    0.74272513      3              1           1            -2             2
## 76    0.26481782      2              1           1            -1             1
## 77    1.60422605      4              3           4             0             1
## 78    1.13987909      2              1           2             0             1
## 79    1.14612804      3              2           3             0             1
## 80    0.46239800      3              2           2            -1             1
## 81    0.23804610      2              0           1            -1             2
## 82    1.50785587      5              4           5             0             1
## 83    0.71349054      3              2           2            -1             1
## 84    0.57054294      3              2           3             0             1
## 85    0.84010609      3              2           3             0             1
## 86    0.68394713      2              1           2             0             1
## 87    1.11394335      4              3           4             0             1
## 88    1.52762990      4              3           4             0             1
## 89    0.38021124      2              1           2             0             1
## 90    0.50105926      4              0           1            -3             4
## 91    0.48144263      3              1           1            -2             2
## 92    1.23299611      4              2           3            -1             2
## 93    0.11727130      3              0           2            -1             3
## 94    1.27646180      3              2           2            -1             1
## 95    0.20139712      3              1           2            -1             2
## 96    1.11058971      4              2           2            -2             2
## 97    1.07188201      3              2           2            -1             1
## 98    1.14921911      3              2           2            -1             1
## 99    3.24054925      4              2           1            -3             2
## 100   2.83122969      4              2           2            -2             2
## 101   3.00000000      4              1           5             1             3
## 102   2.81224470      3              2           3             0             1
## 103   1.68574174      4              2           4             0             2
## 104   2.01703334      4              2           4             0             2
## 105   0.55022835      3              1           4             1             2
## 106   1.59659710      4              2           2            -2             2
## 107   0.95664858      2              1           2             0             1
## 108   1.63042788      3              1           2            -1             2
## 109   0.26951294      2              1           0            -2             1
## 110   2.56110138      2              1           2             0             1
## 111   1.20139712      2              1           2             0             1
## 112   4.51851394      4              1           4             0             3
## 113   1.20139712      2              0           0            -2             2
## 114   1.20139712      3              0           3             0             3
## 115   4.66838592      5              4           5             0             1
## 116   3.61172331      3              2           3             0             1

Permissive idiosyncrasy: When positive epistasis enables node visitation AND mean epistasis would have prevented it

adaptive_traj_access %>%
  drop_na() %>%
  filter(avg > log10(1.5) & access_w_idio > 0 & access_w_mean < 0 & means < 0)
##    genotype       avg                     pos mutations likely
## 1    xxx0xx 2.5755328      p1|p21|p26|p30|p94         5  FALSE
## 2    xx0xxx 3.1289862      p1|p21|p28|p30|p94         5  FALSE
## 3    xx000x 1.0635938              p1|p21|p94         3  FALSE
## 4    x0xxx0 0.2566377          p1|p26|p28|p30         4  FALSE
## 5    x0xxxx 0.5135761      p1|p26|p28|p30|p94         5  FALSE
## 6    x0x0xx 0.2071172          p1|p26|p30|p94         4  FALSE
## 7    00xx0x 0.7498001             p26|p28|p94         3  FALSE
## 8     xxx0x 0.2309903      p72|p193|p258|p273         4   TRUE
## 9   0xx0x00 0.2287509          p215|p219|p224         3  FALSE
## 10  x0x0xxx 0.2083878 p41|p219|p224|p225|p227         5  FALSE
## 11  xxxx0x0 0.3058285 p41|p215|p219|p222|p225         5  FALSE
## 12  xxx00xx 0.4055680 p41|p215|p219|p225|p227         5  FALSE
## 13  xx0000x 0.4412514           p41|p215|p227         3  FALSE
## 14  x0xxxx0 0.4244484 p41|p219|p222|p224|p225         5  FALSE
## 15  x0xx0xx 0.6719119 p41|p219|p222|p225|p227         5  FALSE
## 16  x00xxxx 0.3339212 p41|p222|p224|p225|p227         5  FALSE
## 17  x00x00x 0.4093652           p41|p222|p227         3  FALSE
## 18  x0000xx 0.3800391           p41|p225|p227         3  FALSE
## 19     00xx 0.2092675               p212|p213         2  FALSE
## 20   xxx0x0 0.1837956       p66|p76|p124|p156         4  FALSE
## 21   x00xx0 0.1772274           p67|p158|p180         3  FALSE
## 22   xxx0x0 0.8786927     p233|p254|p271|p306         4   TRUE
## 23   xxx00x 0.9425507     p233|p254|p271|p313         4  FALSE
## 24   0xxx0x 0.2459981     p254|p271|p272|p313         4  FALSE
## 25    00xx0 0.1815151               p104|p182         2  FALSE
## 26    0x0x0 1.2923763                p42|p182         2  FALSE
##               unique_id enzyme_name measure_type      cond        means
## 1      DHFR_ic75_palmer        DHFR         ic75    palmer -1.019035014
## 2      DHFR_ic75_palmer        DHFR         ic75    palmer -0.465581551
## 3      DHFR_ic75_palmer        DHFR         ic75    palmer -0.373479384
## 4      DHFR_ic75_palmer        DHFR         ic75    palmer -1.177492205
## 5      DHFR_ic75_palmer        DHFR         ic75    palmer -3.080991709
## 6      DHFR_ic75_palmer        DHFR         ic75    palmer -0.045612248
## 7      DHFR_ic75_palmer        DHFR         ic75    palmer -0.043087603
## 8      MPH_catact_ZnPTM         MPH       catact     ZnPTM -0.118379979
## 9        NfsA_ec50_2039        NfsA         ec50      2039 -0.036461257
## 10       NfsA_ec50_2039        NfsA         ec50      2039 -0.039287044
## 11       NfsA_ec50_3637        NfsA         ec50      3637 -0.182582709
## 12       NfsA_ec50_3637        NfsA         ec50      3637 -0.048249881
## 13       NfsA_ec50_3637        NfsA         ec50      3637 -0.181880262
## 14       NfsA_ec50_3637        NfsA         ec50      3637 -0.198513642
## 15       NfsA_ec50_3637        NfsA         ec50      3637 -0.109238294
## 16       NfsA_ec50_3637        NfsA         ec50      3637 -0.078881834
## 17       NfsA_ec50_3637        NfsA         ec50      3637 -0.055554618
## 18       NfsA_ec50_3637        NfsA         ec50      3637 -0.360855472
## 19 OXA-48_ic50_CAZtraj1      OXA-48         ic50  CAZtraj1 -0.001843610
## 20 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2 -0.002308696
## 21 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3 -0.010609253
## 22       PTE_catact_2NH         PTE       catact       2NH -0.333523949
## 23       PTE_catact_2NH         PTE       catact       2NH -0.226875448
## 24       PTE_catact_2NH         PTE       catact       2NH -0.230150706
## 25    TEM_MIC_weinreich         TEM          MIC weinreich -0.638009314
## 26    TEM_MIC_weinreich         TEM          MIC weinreich -0.253191980
##    traj_effects access access_no_idio access_mean access_w_mean access_w_idio
## 1     2.3138672      5              0           0            -5             5
## 2     2.2787536      4              2           2            -2             2
## 3     1.9831751      3              1           0            -3             2
## 4     2.3222193      3              0           0            -3             3
## 5     2.3242825      4              1           0            -4             3
## 6     2.2174839      4              1           1            -3             3
## 7     2.0492180      2              1           1            -1             1
## 8     2.3117539      4              3           3            -1             1
## 9    -0.1313556      2              0           0            -2             2
## 10    0.8674675      5              4           2            -3             1
## 11    0.9350032      5              3           2            -3             2
## 12    0.8363241      4              1           1            -3             3
## 13    0.3138672      3              1           1            -2             2
## 14    1.0000000      5              1           1            -4             4
## 15    0.8830934      4              0           0            -4             4
## 16    0.8007171      5              1           1            -4             4
## 17    0.3483049      3              1           1            -2             2
## 18    0.7427251      3              1           1            -2             2
## 19    0.2648178      2              1           1            -1             1
## 20    0.7134905      3              2           2            -1             1
## 21    1.0718820      3              2           2            -1             1
## 22    3.2405492      4              2           1            -3             2
## 23    2.8312297      4              2           2            -2             2
## 24    1.5965971      4              2           2            -2             2
## 25    0.2695129      2              1           0            -2             1
## 26    1.2013971      2              0           0            -2             2

Even more interesting are the nodes with are either ENTIRELY accessible or inaccessible due to epistasis

adaptive_traj_access %>%
  drop_na() %>%
  filter(avg > log10(1.5) & access_no_idio == 0 & access > 0)
##    genotype        avg                               pos mutations likely
## 1    xxxx0x 10.4358638                p1|p21|p26|p28|p94         5  FALSE
## 2    xxx0xx  2.5755328                p1|p21|p26|p30|p94         5  FALSE
## 3    x0xxx0  0.2566377                    p1|p26|p28|p30         4  FALSE
## 4    x00x0x  1.0706822                        p1|p28|p94         3  FALSE
## 5    0xx00x  5.0316956                       p21|p26|p94         3  FALSE
## 6     x0xxx  1.8737920                   p21|p28|p30|p94         4  FALSE
## 7     x00xx  0.9335231                     p72|p271|p273         3  FALSE
## 8   0xx0x00  0.2287509                    p215|p219|p224         3  FALSE
## 9   0xx00x0  0.4841288                    p215|p219|p225         3  FALSE
## 10  xxxxx0x  0.1907594      p41|p215|p219|p222|p224|p227         6  FALSE
## 11  xx00x00  0.2626518                     p41|p215|p224         3  FALSE
## 12  x0x0x00  0.1951751                     p41|p219|p224         3  FALSE
## 13  0xxx00x  0.3133913               p215|p219|p222|p227         4  FALSE
## 14  0xx0x0x  0.2739510               p215|p219|p224|p227         4  FALSE
## 15  0x0xx0x  0.2141675               p215|p222|p224|p227         4  FALSE
## 16  0x0000x  0.2929325                         p215|p227         2  FALSE
## 17  00x0x00  0.2124097                         p219|p224         2  FALSE
## 18  xxxxxxx  1.9130555 p41|p215|p219|p222|p224|p225|p227         7   TRUE
## 19  xxxx00x  0.7515982           p41|p215|p219|p222|p227         5  FALSE
## 20  xxx0x0x  0.5787185           p41|p215|p219|p224|p227         5  FALSE
## 21  xx0xx0x  0.4530458           p41|p215|p222|p224|p227         5  FALSE
## 22  xx0x0xx  0.7581143           p41|p215|p222|p225|p227         5  FALSE
## 23  x0xxx0x  0.7129843           p41|p219|p222|p224|p227         5  FALSE
## 24  x0xx0xx  0.6719119           p41|p219|p222|p225|p227         5  FALSE
## 25  x000x0x  0.5949846                     p41|p224|p227         3  FALSE
## 26   x0x0xx  0.4265923                p66|p124|p156|p243         4  FALSE
## 27   0xxxxx  0.4960242          p142|p154|p158|p180|p215         5  FALSE
## 28   xxx0x0  0.2375477                p67|p142|p154|p180         4  FALSE
## 29    0x0x0  1.2923763                          p42|p182         2  FALSE
## 30    xxxx0  1.4522693               p4205|p42|p104|p182         4  FALSE
##               unique_id enzyme_name measure_type      cond       means
## 1      DHFR_ic75_palmer        DHFR         ic75    palmer  6.84129599
## 2      DHFR_ic75_palmer        DHFR         ic75    palmer -1.01903501
## 3      DHFR_ic75_palmer        DHFR         ic75    palmer -1.17749221
## 4      DHFR_ic75_palmer        DHFR         ic75    palmer  1.64784156
## 5      DHFR_ic75_palmer        DHFR         ic75    palmer  1.69529922
## 6         DHFR_ki_trajg        DHFR           ki     trajg  1.67259092
## 7      MPH_catact_ZnPTM         MPH       catact     ZnPTM  1.13823460
## 8        NfsA_ec50_2039        NfsA         ec50      2039 -0.03646126
## 9        NfsA_ec50_2039        NfsA         ec50      2039  0.35177779
## 10       NfsA_ec50_2039        NfsA         ec50      2039  0.30651198
## 11       NfsA_ec50_2039        NfsA         ec50      2039  0.08912188
## 12       NfsA_ec50_2039        NfsA         ec50      2039  0.05163206
## 13       NfsA_ec50_3637        NfsA         ec50      3637  0.16030008
## 14       NfsA_ec50_3637        NfsA         ec50      3637  0.09261463
## 15       NfsA_ec50_3637        NfsA         ec50      3637  0.01220592
## 16       NfsA_ec50_3637        NfsA         ec50      3637  0.18769791
## 17       NfsA_ec50_3637        NfsA         ec50      3637  0.07485416
## 18       NfsA_ec50_3637        NfsA         ec50      3637  1.91305548
## 19       NfsA_ec50_3637        NfsA         ec50      3637  0.20663486
## 20       NfsA_ec50_3637        NfsA         ec50      3637  0.22653671
## 21       NfsA_ec50_3637        NfsA         ec50      3637  0.27642964
## 22       NfsA_ec50_3637        NfsA         ec50      3637  0.47986213
## 23       NfsA_ec50_3637        NfsA         ec50      3637  0.03347017
## 24       NfsA_ec50_3637        NfsA         ec50      3637 -0.10923829
## 25       NfsA_ec50_3637        NfsA         ec50      3637  0.12064083
## 26 OXA-48_ic50_CAZtraj2      OXA-48         ic50  CAZtraj2  0.38623823
## 27 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.25971748
## 28 OXA-48_ic50_CAZtraj3      OXA-48         ic50  CAZtraj3  0.16493203
## 29    TEM_MIC_weinreich         TEM          MIC weinreich -0.25319198
## 30    TEM_MIC_weinreich         TEM          MIC weinreich  1.58700601
##    traj_effects access access_no_idio access_mean access_w_mean access_w_idio
## 1    2.29446623      3              0           1            -2             3
## 2    2.31386722      5              0           0            -5             5
## 3    2.32221929      3              0           0            -3             3
## 4    2.28330123      3              0           3             0             3
## 5    1.36361198      3              0           1            -2             3
## 6    4.19865709      4              0           4             0             4
## 7    0.34830486      2              0           2             0             2
## 8   -0.13135556      2              0           0            -2             2
## 9   -0.08144547      2              0           1            -1             2
## 10  -0.14448084      2              0           4             2             2
## 11  -0.07160415      2              0           0            -2             2
## 12   0.04139269      2              0           1            -1             2
## 13   0.11394335      2              0           1            -1             2
## 14  -0.10790540      2              0           0            -2             2
## 15  -0.07160415      2              0           0            -2             2
## 16   0.14301480      2              0           2             0             2
## 17  -0.10182352      1              0           1             0             1
## 18   1.00432137      7              0           7             0             7
## 19   0.72345567      5              0           2            -3             5
## 20   0.10380372      4              0           0            -4             4
## 21  -0.01863449      3              0           0            -3             3
## 22   0.85186960      5              0           2            -3             5
## 23   0.10720997      4              0           0            -4             4
## 24   0.88309336      4              0           0            -4             4
## 25  -0.01637371      3              0           0            -3             3
## 26   0.23804610      2              0           1            -1             2
## 27   0.50105926      4              0           1            -3             4
## 28   0.11727130      3              0           2            -1             3
## 29   1.20139712      2              0           0            -2             2
## 30   1.20139712      3              0           3             0             3
adaptive_traj_access %>%
  drop_na() %>%
  filter(avg < log10(1/1.5) & access_no_idio > 0 & access == 0)
##    genotype        avg                 pos mutations likely
## 1    xx0x0x -5.2140863      p1|p21|p28|p94         4  FALSE
## 2    0xx000 -4.0673669             p21|p26         2  FALSE
## 3    0xxx0x -4.7257532     p21|p26|p28|p94         4  FALSE
## 4    0x0xx0 -1.6714200         p21|p28|p30         3  FALSE
## 5    0x00xx -1.5696224         p21|p30|p94         3  FALSE
## 6    000xxx -2.0436471         p28|p30|p94         3  FALSE
## 7   0x000x0 -0.8913091           p215|p225         2  FALSE
## 8   x000x00 -0.1999418            p41|p224         2  FALSE
## 9   0x000x0 -0.7363049           p215|p225         2  FALSE
## 10  x00xx00 -0.3562048       p41|p222|p224         3  FALSE
## 11  x00000x -0.4283630            p41|p227         2  FALSE
## 12   x0x00x -0.4946517       p66|p124|p243         3  FALSE
## 13   xxx000 -0.2525100       p67|p142|p154         3  FALSE
## 14   x00xxx -0.9373094 p233|p272|p306|p313         4  FALSE
##               unique_id enzyme_name measure_type     cond       means
## 1      DHFR_ic75_palmer        DHFR         ic75   palmer -0.22894521
## 2      DHFR_ic75_palmer        DHFR         ic75   palmer  0.53515465
## 3      DHFR_ic75_palmer        DHFR         ic75   palmer -0.82781359
## 4      DHFR_ic75_palmer        DHFR         ic75   palmer  0.76025803
## 5      DHFR_ic75_palmer        DHFR         ic75   palmer  0.27945161
## 6      DHFR_ic75_palmer        DHFR         ic75   palmer  0.68005918
## 7        NfsA_ec50_2039        NfsA         ec50     2039 -0.24105803
## 8        NfsA_ec50_2039        NfsA         ec50     2039  0.05849991
## 9        NfsA_ec50_3637        NfsA         ec50     3637 -0.17123523
## 10       NfsA_ec50_3637        NfsA         ec50     3637 -0.11793908
## 11       NfsA_ec50_3637        NfsA         ec50     3637 -0.05626247
## 12 OXA-48_ic50_CAZtraj2      OXA-48         ic50 CAZtraj2 -0.13701889
## 13 OXA-48_ic50_CAZtraj3      OXA-48         ic50 CAZtraj3 -0.10303183
## 14       PTE_catact_2NH         PTE       catact      2NH -0.27806987
##    traj_effects access access_no_idio access_mean access_w_mean access_w_idio
## 1  -3.031517051      0              3           1             1            -3
## 2  -3.031517051      0              2           2             2            -2
## 3  -0.422508200      0              4           4             4            -4
## 4  -0.804100348      0              1           2             2            -1
## 5  -0.543633967      0              2           2             2            -2
## 6  -0.157390760      0              2           3             3            -2
## 7  -0.501689446      0              1           1             1            -1
## 8  -0.151810883      0              1           2             2            -1
## 9  -0.327902142      0              1           1             1            -1
## 10 -0.287350298      0              2           2             2            -2
## 11 -0.449771647      0              1           1             1            -1
## 12  0.100370545      0              2           2             2            -2
## 13 -0.008773924      0              3           2             2            -3
## 14  0.474216264      0              3           1             1            -3

Specific epistasis examples, starting with PTE

with_epi = fit_land %>%
  filter(unique_id == "PTE_catact_2NH" & id == "111010") %>%
  pull(effect)

epi = higher_df %>% filter(partial_id == "PTE_catact_2NH" & genotype == "xxx0x0") %>% pull(avg)
mean_epi = adaptive_traj %>% filter(unique_id == "PTE_catact_2NH" & genotype == "xxx0x0") %>% pull(means)

wo_epi = with_epi - epi
w_mean_epi = with_epi - epi + mean_epi

fig_4_new = fit_land %>%
  filter(unique_id == "PTE_catact_2NH") %>%
  filter(id == "000010" | id == "010010" | id == "110010" | id == "111010" | id == "111110" | id == "111111") %>%
  add_row(id = "000000", 
          effect = 0, 
          muts = 0, 
          junk1 = NA, 
          junk2 = NA, 
          enz = "PTE", 
          unique_id = "PTE_catact_2NH",
          .before = 1) %>%
  add_row(id = "alt", 
          effect = wo_epi, 
          muts = 4, 
          junk1 = NA, 
          junk2 = NA, 
          enz = "PTE", 
          unique_id = "PTE_catact_2NH",
          .before = 1) %>%
  add_row(id = "alt2", 
          effect = w_mean_epi, 
          muts = 4, 
          junk1 = NA, 
          junk2 = NA, 
          enz = "PTE", 
          unique_id = "PTE_catact_2NH",
          .before = 1) %>%
  select(-c("junk1", "junk2")) %>%
  mutate(muts = factor(muts)) %>%
  ggplot(aes(x = muts, y = effect)) +
  geom_point(shape = 1, size = 3) +
  labs(x = "Step",
       y = expression("log"[10]*" Function") ) +
  theme_classic() +
  theme(axis.line = element_line(size = 0.2, color = "black"), 
        axis.ticks = element_line(size = 0.2, color = "black"), 
        text = element_text(size = 9), 
        axis.text = element_text(size = 8, color = "black"))

fig_4_new

#ggsave("fig_4A_new.svg", fig_4_new, width = 180/2.5, height = 247/4, dpi = 300, units = "mm")

Next one is MPH

with_epi = fit_land %>%
  filter(unique_id == "MPH_catact_ZnPTM" & id == "10001") %>%
  pull(effect)

epi = higher_df %>% filter(partial_id == "MPH_catact_ZnPTM" & genotype == "x000x") %>% pull(avg)
mean_epi = adaptive_traj %>% filter(unique_id == "MPH_catact_ZnPTM" & genotype == "x000x") %>% pull(means)

wo_epi = with_epi - epi
w_mean_epi = with_epi - epi + mean_epi

fig_4b_new = fit_land %>%
  filter(unique_id == "MPH_catact_ZnPTM") %>%
  filter(id == "10000" | id == "10001" | id == "11001" | id == "11101" | id == "11111") %>%
  add_row(id = "00000", 
          effect = 0, 
          muts = 0, 
          junk1 = NA, 
          junk2 = NA, 
          enz = "MPH", 
          unique_id = "MPH_catact_ZnPTM",
          .before = 1) %>%
  add_row(id = "alt", 
          effect = wo_epi, 
          muts = 2, 
          junk1 = NA, 
          junk2 = NA, 
          enz = "MPH", 
          unique_id = "MPH_catact_ZnPTM") %>%
  add_row(id = "alt2", 
          effect = w_mean_epi, 
          muts = 2, 
          junk1 = NA, 
          junk2 = NA, 
          enz = "MPH", 
          unique_id = "MPH_catact_ZnPTM") %>%
  select(-c("junk1", "junk2")) %>%
  mutate(muts = factor(muts)) %>%
  ggplot(aes(x = muts, y = effect)) +
  geom_point(shape = 1, size = 3) +
  labs(x = "Step",
       y = expression("log"[10]*" Function") ) +
  theme_classic() +
  theme(axis.line = element_line(size = 0.2, color = "black"), 
        axis.ticks = element_line(size = 0.2, color = "black"), 
        text = element_text(size = 9), 
        axis.text = element_text(size = 8, color = "black"))

fig_4b_new

#ggsave("fig_4B_new.svg", fig_4b_new, width = 180/2.5, height = 247/4, dpi = 300, units = "mm")

Correlation between F and epistasis

Here we attempt to see whether the function of the genotype F is an indicator of the magnitude of epistasis

higher_df_start_to_epi = higher_df %>%
  unite("partial_id", c(Enzyme, Measurement, Condition)) %>%
  mutate(from = str_replace_all(genotype, "x", "0"),
         to = str_replace_all(genotype, "x", "1"))

start_effect = c()
for(i in 1:dim(higher_df_start_to_epi)[1]) {
  
  if(!str_detect(higher_df_start_to_epi$from[i], "1")) {
    start_effect = c(start_effect, 0) # If starts from WT, start effect is 0
  } else {
    start_effect = c(start_effect, filter(fit_land, unique_id == higher_df_start_to_epi$partial_id[i] & id == higher_df_start_to_epi$from[i]) 
  %>% pull(effect))
  }
}

higher_df_start_to_epi$start_effect = start_effect

The higher_df_start_to_epi tibble contains information regarding specific epistasis in the avg variable and starting effect of the genotype in the start_effect. We can plot the correlation for all landscapes

higher_df_start_to_epi %>%
  filter(mutations > 1) %>%
  ggplot(aes(x = start_effect, y = avg)) +
  geom_point() +
  theme_classic()

Then again for adaptive landscapes only

higher_df_start_to_epi %>%
  filter(mutations > 1 & partial_id %in% adaptive_trajectories) %>%
  ggplot(aes(x = start_effect, y = avg)) +
  geom_point() +
  theme_classic()

What if we facet adaptive landscapes by order?

higher_df_start_to_epi %>%
  filter(mutations > 1 & partial_id %in% adaptive_trajectories) %>%
  ggplot(aes(x = start_effect, y = avg)) +
  geom_point() +
  facet_wrap(~ mutations) +
  theme_classic()

Due to the differences in strength of functional affects across landscapes, maybe its important to separate by landscape and see whether there is a difference between the correlation of mutation effects and starting function VS the correlation of epistasis and starting function

trajectory_names = c(
  DHFR_ic75_palmer = "DHFR Palmer et al.",
  DHFR_ki_trajg = "DHFR Traj. G",
  DHFR_ki_trajr = "DHFR Traj. R",
  MPH_catact_ZnPTM = "MPH Traj. Zn",
  NfsA_ec50_2039 = "NfsA Traj. 20_39",
  NfsA_ec50_3637 = "NfsA Traj. 36_37",
  `OXA-48_ic50_CAZtraj1` = "OXA-48 CAZ Traj. 1",
  `OXA-48_ic50_CAZtraj2` = "OXA-48 CAZ Traj. 2",
  `OXA-48_ic50_CAZtraj3` = "OXA-48 CAZ Traj. 3",
  PTE_catact_2NH = "PTE Traj. 2NH",
  TEM_MIC_weinreich = "TEM Weinreich et al.")

global_labeller = labeller(
  partial_id = trajectory_names
)

dimish_del_f = higher_df_start_to_epi %>%
  filter(mutations == 1 & partial_id %in% adaptive_trajectories) %>%
  ggplot(aes(x = start_effect, y = avg)) +
  stat_cor(aes(label = paste(..r.label.., sep = "~~")), method = "spearman", cor.coef.name = "rho", label.x.npc = "middle",
  label.y.npc = "top", r.accuracy = 0.01, size = 2.5, color = "black") +
  geom_point() +
  geom_smooth(method = 'loess', formula = y ~ x) +
  facet_wrap(~ partial_id,
             scales = "free",
             labeller = global_labeller) +
  theme_classic() +
  labs(x = expression("Starting Function ("*italic("F")*")"), 
       y = expression(Delta*italic("F"))) +
  theme(text = element_text(size=9), axis.text = element_text(size=8, color = "black"),
        legend.position = "none", axis.line=element_line()) #+ 
 # scale_y_continuous(limits=c(-5,5)) +
  #scale_x_continuous(limits=c(-3,5))

dimish_epi = higher_df_start_to_epi %>%
  filter(mutations > 1 & partial_id %in% adaptive_trajectories) %>%
  ggplot(aes(x = start_effect, y = avg)) +
  stat_cor(aes(label = paste(..r.label.., sep = "~~")), method = "spearman", cor.coef.name = "rho", label.x.npc = "middle",
  label.y.npc = "top", r.accuracy = 0.01, size = 2.5, color = "black") +
  geom_point() +
  geom_smooth(method = 'loess', formula = y ~ x) +
  facet_wrap(~ partial_id,
             scales = "free",
             labeller = global_labeller) +
  theme_classic() +
  labs(x = expression("Starting Function ("*italic("F")*")"), 
       y = expression(epsilon)) +
  theme(text = element_text(size=9), axis.text = element_text(size=8, color = "black"),
        legend.position = "none", axis.line=element_line())

dimish_del_f

dimish_epi

#ggsave("supp_fig_3A.svg", dimish_del_f, width = 180, height = 247/2, dpi = 300, units = "mm")
#ggsave("supp_fig_3B.svg", dimish_epi, width = 180, height = 247/2, dpi = 300, units = "mm")